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Introduction: The opioid epidemic is a major cause of morbidity and mortality in the United States. Prior work has shown that emergency department (ED) opioid prescribing can increase the incidence of opioid use disorder in a dose-dependent manner, and systemic changes that decrease default quantity of discharge opioid tablets in the electronic health record (EHR) can impact prescribing practices. However, ED leadership may be interested in the impact of communication around the intervention as well as whether the intervention may differentially impact different types of clinicians (physicians, physician assistants [PA], and nurse practitioners). We implemented and evaluated a quality improvement intervention of an announced decrease in EHR default quantities of commonly prescribed opioids at a large, academic, urban, tertiary-care ED.Methods: We gathered EHR data on all ED discharges with opioid prescriptions from January 1, 2019–December 6, 2021, including chief complaint, clinician, and opioid prescription details. Data was captured and analyzed on a monthly basis throughout this time period. On March 29, 2021, we implemented an announced decrease in EHR default dispense quantities from 20 tablets to 12 tablets for commonly prescribed opioids. We measured pre- and post-intervention quantities of opioid tablets prescribed per discharge receiving opioids, distribution by patient demographics, and inter-clinician variability in prescribing behavior.Results: The EHR change was associated with a 14% decrease in quantity of opioid tablets per discharge receiving opioids, from 14 to 12 tablets (P =

Recently, various pesticides have been employed at different stages of cultivation to protect the oil crop from insect, disease, and weed. Those pesticides, especially lipophilic ones, bio-accumulate in the oilseeds and get co-extracted into edible oils during the refining process. Hence, this study aimed to optimise an extraction method for routine pesticide multi-residue analysis in edible vegetable oil samples using gas chromatography coupled to tandem mass spectrometry (GC – MS/MS). Two parameters were optimised using a factorial design of experiment (solvent type and solvent/sample ratio). In general, the number of pesticides that conformed to our criteria (mean recovery 70–120%) increased as the solvent/sample ratio increased. Each of the three tested solvents had an advantage over the other, ethyl acetate showed the highest capability for non-polar pesticides extraction, acetonitrile had the highest sensitivity, and the ethyl acetate/acetonitrile mixture showed the highest number of pesticides with acceptable criteria. The three solvents were tested using two different cleanup sorbents (EMR, and Z-Sep), the best solvent/cleanup combination was found to be ethyl acetate/acetonitrile mixture in addition to Z-Sep. The final method was validated in accordance with the European guidelines for Analytical Quality Control and Method Validation Procedures for Pesticide Residues Analysis in Food and Feed (SANTE/11312/2021). The precision and trueness of the method were determined from recovery experiments on six replicates of spiked blank corn oil samples at 0.01, 0.025, and 0.05 mg/kg. The number of pesticides that showed accepted criteria were 130, 166, and 182 out of 222 for each spiking level respectively. [ABSTRACT FROM AUTHOR]

Background: Electronic medical records (EMR)-trained machine learning models have the potential in CVD risk prediction by integrating a range of medical data from patients, facilitate timely diagnosis and classification of CVDs. We tested the hypothesis that unsupervised ML approach utilizing EMR could be used to develop a new model for detecting prevalent CVD in clinical settings. Methods: We included 155,894 patients (aged ≥ 18 years) discharged between January 2014 and July 2022, from Xuhui Hospital, Shanghai, China, including 64,916 CVD cases and 90,979 non-CVD cases. K-means clustering was used to generate the clustering models with k = 2, 4, and 8 as predetermined number of clusters k = 2, 4, and 8. Bayesian theorem was used to estimate the models' predictive accuracy. Results: The overall predictive accuracy of the 2-, 4-, and 8-classification clustering models in the training set was 0.856, 0.8634, and 0.8506, respectively. Similarly, the predictive accuracy of the 2-, 4-, and 8-classification clustering models in the testing set was 0.8598, 0.8659, and 0.8525, respectively. After reducing from 19 dimensions to 2 dimensions by principal component analysis, significant separation was observed for CVD cases and non-CVD cases in both training and testing sets. Conclusion: Our findings indicate that the utilization of EMR data can support the development of a robust model for CVD detection through an unsupervised ML approach. Further investigation using longitudinal design is needed to refine the model for its applications in clinical settings. [ABSTRACT FROM AUTHOR]

The QuEChERS extraction method was extensively modified and validated for effective screening of drugs and pesticides in diverse biological matrices, such as blood, urine, liver, and stomach contents. This method involved the extraction of 2 mL biological samples using acetonitrile as the solvent. To eliminate interferences, particularly lipids, a novel sorbent comprising a combination of C18 and specialized polymers called EMR-L (Enhanced Matrix Removal-Lipid) was employed. The extracted samples were then subjected to analysis using GCMS with a DB-5 MS column. The validation study encompassed various parameters including carryover, limit of detection (LOD), and interference investigation. LOD of analytes were ranged from 0.5 to 1.0 µg/mL. The validated method is known for its simplicity and effectiveness in conducting systemic toxicological analysis, covering a wide range of acidic, neutral, and basic analytes. Moreover, this method has the potential to detect additional drugs and pesticides not included in the validation study, provided they are compatible with gas chromatographic analysis. The modified method was successfully applied to real case samples, proving to be a valuable tool for systemic toxicological analysis. Its versatility allows for the screening of acidic, neutral, and basic drugs and pesticides in various biological matrices. [ABSTRACT FROM AUTHOR]

For an emerging infectious disease such as 2019 coronavirus disease (COVID-19), initially there may not be any existing medication or treatment immediately available, which may result in high morbidity and mortality in a short time of period. In this case, it is urgent to quickly identify whether existing medications or treatments could be repurposed to treat the newly appeared disease before time-consuming randomized clinical trials (RCTs) can be done and new drugs can be developed. For example, when SARS-CoV-2 appeared in late 2019, clinicians started to use existing antiviral drugs, anti-inflammatory drugs, immune-based therapies and other types of medications to treat COVID-19 patients before any data or evidence was available to support the use of these medications for the new COVID-19 disease. Most of these medications have proven to be ineffective or only marginally effective to treat COVID-19 patients by more rigorous RCT or secondary data analyses later. We propose to use real-world electronic medical records (EMR) data to develop real-time treatment evaluation and monitoring systems to identify effective treatments or avoid ineffective treatments for emerging diseases in the future. In order to do this, first we have to deal with the challenges in processing and analyzing complex and noisy EMR data. In this paper, we outline these challenges and propose practical statistical methods and guidelines, which are derived from a project in evaluating anti-viral medication, remdesivir, for COVID-19 treatment based on a local healthcare EMR database. [ABSTRACT FROM AUTHOR]

Background and aims: Palliative care in the Eastern Mediterranean Region (EMR) faces challenges despite the high number of patients in need. To provide accessible, affordable, and timely services, it is crucial to adopt a suitable care model. World health organization (WHO) recommends integrating palliative care with primary health care (PHC). Given the unique conditions of EMR countries, there is a need to design a model tailored to these contexts. Methods: This study is a multi-method research project conducted through several sub-studies, including a literature review, policy analysis, expert opinion (Delphi Method), dimension-specific analysis, model development, and its validation and refinement (Delphi Method). Drawing from the WHO model, six dimensions: policy, drug availability, education, community integration, service delivery, and research were considered to developing the model and implementation requirements. Within each dimension, evidence-based solutions tailored to the region's context were explored. Results: A successful palliative care model requires, in the policy dimension, oversight by the Ministry of Health (MOH). Having a focal-person or working group within the MOH is crucial for policy-making, formulation, and approval of clinical guidelines, as well as addressing care challenges. It is essential to provide access to morphine and other essential medications, along with facilitating the administration and consumption of morphine at home. Conducting empowerment courses for care providers, can address various challenges. Community involvement through volunteers, charities, and non-governmental organizations (NGOs) is also important. To ensure service provision, monitoring and evaluating systems are crucial, along with striving for service continuity through an appropriate payment system. Lastly, research is necessary for needs assessment, evidence-based practice, and designing evaluation indicators. The proposed model relies on community health workers, especially nurses, as multitasking professionals available for community palliative care. In the presented model, special attention has been given to networking, collaboration, and the use of digital health technologies to support nurses. Conclusion: The model proposed for integrating palliative care into PHC should serve as a framework that enhances access to available and affordable services for countries in the region. While this model was developed based on the overall conditions of the region, each country can tailor it to its unique strengths and opportunities. [ABSTRACT FROM AUTHOR]

Abstract Background Blood management is an important aspect of healthcare and vital for the well-being of patients. For effective blood management, it is essential to determine the quality and documentation of the processes for blood transfusions in the Electronic Medical Records (EMR) system. The EMR system stores information on most activities performed in a digital hospital. As such, it is difficult to get an overview of all data. The National Safety and Quality Health Service (NSQHS) Standards define metrics that assess the care quality of health entities such as hospitals. To produce these metrics, data needs to be analysed historically. However, data in the EMR is not designed to easily perform analytical queries of the kind which are needed to feed into clinical decision support tools. Thus, another system needs to be implemented to store and calculate the metrics for the blood management national standard. Methods In this paper, we propose a clinical data warehouse that stores the transformed data from EMR to be able to identify that the hospital is compliant with the Australian NSQHS Standards for blood management. Firstly, the data needed was explored and evaluated. Next, a schema for the clinical data warehouse was designed for the efficient storage of EMR data. Once the schema was defined, data was extracted from the EMR to be preprocessed to fit the schema design. Finally, the data warehouse allows the data to be consumed by decision support tools. Results We worked with Eastern Health, a major Australian health service, to implement the data warehouse that allowed us to easily query and supply data to be ingested by clinical decision support systems. Additionally, this implementation provides flexibility to recompute the metrics whenever data is updated. Finally, a dashboard was implemented to display important metrics defined by the National Safety and Quality Health Service (NSQHS) Standards on blood management. Conclusions This study prioritises streamlined data modeling and processing, in contrast to conventional dashboard-centric approaches. It ensures data readiness for decision-making tools, offering insights to clinicians and validating hospital compliance with national standards in blood management through efficient design.

This study investigates the changes in electromagnetic radiation (EMR) emissions from cement-mortar subjected to impact throughout its curing process. The generation of EMR signals in hydrated samples is primarily driven by the accelerated motion of charged particles through the pore spaces and the time-dependent variation in dipole moments formed at the electrical double layer. As the hydration (curing) progresses, there is a noticeable decrease in EMR voltage, average EMR energy release rate, and dominant frequency. However, these EMR parameters exhibit an increasing trend with the application of higher mechanical impact energy. It was further observed that as hydration advances, the non-evaporable water content and degree of hydration increase, whereas the evaporable water content decreases. Additionally, EMR voltage recorded after fracture was consistently lower than that measured before fracture across all curing days, indicating that crack formation during repetitive loading suppresses EMR emissions. This suggests that cracks formed in the cement-mortar do not facilitate EMR generation. Moreover, the study found an inverse relationship between impact-dependent mechanical parameters and EMR voltage, highlighting that as mechanical resistance to impact increases, EMR voltage decreases. These findings suggest that the EMR technique has significant potential for non-contact, early-age monitoring of civil structures, providing critical insights into their mechanical integrity and performance under load. [ABSTRACT FROM AUTHOR]

This paper represents a wide incident angle-polarization insensitive, stable in results, and compact-sized metamaterial absorber that can be used for Doppler navigation aids and remote sensing applications in Earth Exploration Satellite Services. The unit cell dimension was subwavelength-sized of 0.112λ X 0.112λ, with a good effective medium ratio (8.9), and achieved polarization insensitivity at a maximum incident angle up to 180°, making it more effective for proposed applications. The absorber resonated at 3.855 GHz, 5.13 GHz, 9.855 GHz, 13.335 GHz, and 16.02 GHz with single negative metamaterial properties due to negative permeability and absorptions of 99.7 %, 99.2 %, 98.6 %, 98.1 %, and 97.9 %, respectively. An RLC equivalent circuit on ADS was analyzed to validate the simulated results using the dipoles created by the surface currents. The absorber is cost-effective as no lumped elements or multilayer substrate materials were used, making fabricating less time-consuming and simple. The simulated results were validated by measuring data from a vector network analyzer after fabricating it. The proposed metamaterial absorber is suitable for use in Doppler navigation and Earth Exploration Satellite Services, and this research can further be extended to beamforming and sensing applications in the future.

Simple Summary: The advent of underwater endoscopic resection techniques has served as an add-on for both basic and advanced procedures, since its first report in 2012 till its inclusion into the European Society of Gastrointestinal Endoscopy guidelines. Hence, we aimed to perform a comprehensive update on the state of the art about the feasibility of underwater basic and advanced techniques for GI endoscopy. Underwater endoscopic mucosal resection represents a standard for treating intermediate-size colonic and non-ampullary duodenal lesions. Promising results have been shown in third-space endoscopy studies, even though further prospective studies are awaited to standardise the technique for both endoscopic submucosal dissection and peroral endoscopic myotomy. The endoscopic resection of gastrointestinal tract lesions embraces different types of techniques, ranging from conventional polypectomy/endoscopic mucosal resection (EMR) to the field of third-space endoscopy, including endoscopic submucosal dissection (ESD), full-thickness resection and peroral endoscopic myotomy (POEM). Parallelly, the advent of underwater techniques has served as an add-on for both basic and advanced procedures, since its first report in 2012. We aimed to provide a comprehensive update on the state of the art about the feasibility of underwater basic and advanced techniques for GI endoscopy. Underwater EMR (U-EMR) has proved effective and safe in treating > 10 mm sessile or flat or all-size recurrent colonic lesions. Conversely, although data show good effectiveness and safety for <10 mm lesions, it is preferred when high-grade dysplasia is suspected, favouring cold snare polypectomy for all other cases. Moreover, promising data are emerging regarding the feasibility of U-ESD for difficult-to-resect colonic lesions. U-EMR represents a standard of care for treating < 25 mm superficial non-ampullary duodenal epithelial tumours. Data regarding oesophageal, gastric and ampullary lesions remains limited to small cohorts. Finally, using water immersion for POEM has shown a reduction in procedure time compared to the CO2 insufflation technique for vessel coagulation, albeit in a single-centre experience. Based on these results, U-EMR has become a standard for treating intermediate-size colonic and non-ampullary duodenal lesions, as highlighted also in the European Society of Gastrointestinal Endoscopy guidelines. Promising results have been shown in third-space endoscopy studies, even though further prospective studies are awaited to standardise the technique for both ESD and POEM. [ABSTRACT FROM AUTHOR]

Rationale: Short‐term weight loss is possible in a variety of settings. However, long‐term, free‐living weight loss maintenance following structured weight loss interventions remains elusive. Objective: The purpose was to study body weight trajectories over 2 years of intensive lifestyle intervention (ILI) and up to 4 years of follow‐up versus usual care (UC). Methods: Data were obtained from electronic medical records (EMRs) from participating clinics. Baseline (Day 0) was established as the EMR data point closest but prior to the baseline date of the trial. The sample included 111 ILI and 196 UC patients. The primary statistical analysis focused on differentiating weight loss trajectories between ILI and UC. Results: The ILI group experienced significantly greater weight loss compared with the UC group from Day 100 to Day 700, beyond which there were no significant differences. Intensive lifestyle intervention patients who maintained ≥5% and ≥10% weight loss at 24 months demonstrated significantly greater weight loss (p < 0.001) across the active intervention and follow‐up. Conclusions: Following 24 months of active intervention, patients with ILI regained weight toward their baseline to the point where ILI versus UC differences were no longer statistically or clinically significant. However, patients in the ILI who experienced ≥5% or ≥10% weight loss at the cessation of the active intervention maintained greater weight loss at the end of the follow‐up phase. Clinical Trial Registration: ClinicalTrials.gov: NCT02561221. [ABSTRACT FROM AUTHOR]

Background: Endoscopic resection is currently the treatment of choice for laterally spreading tumors (LSTs). Endoscopic sub-mucosal dissection (ESD) can achieve higher enbloc resection and R0 resection, albeit at a slightly higher risk of complications. Given scarce data on ESD from India, we performed a retrospective analysis of our experience with colorectal ESD (CR-ESD) to know its clinical efficacy and complications as well as to assess the learning curve of CR-ESD in non-endemic-areas. Methods: Retrospective analysis of prospectively maintained datasheet performed. All patients with large (>2cm), complex or recurrent colorectal LST who underwent ESD at our center between 2012 and 2021 were included in the study. Various baseline lesion-related parameters, procedure-related parameters, enbloc resection (ER) rates, R0 margins and adverse event rates were retrieved. CUSUM analysis was performed to calculate the minimum required procedures to achieve competency in CR-ESD. Results: Total 149 patients were included in the study; mean patient age was 61.36±18.21 years. Most patients had lesions in rectum (n=102; 68.5%) followed by sigmoid colon (n=25; 16.8%). The mean lesion size was 46.62 ± 25.46 mm and the mean procedure duration for ESD was 219.30 ± 150.05 min. ER was achieved in 94.6% of lesions. R0 resection was achieved in 132 patients (88.6%). Overall, six (4%) adverse events were noted, of which one required surgical intervention. As many as 105 patients (70.5%) had adenomatous lesions on histology. Seventy-four patients underwent follow-up colonoscopy, of which three had a recurrence of adenomatous lesions and five had post-resection stricture requiring endoscopic dilation. CUSUM curve analysis calculated the learning curve for ESD was 47 resections for ER and 55 for the occurrence of AEs, with a composite CUSUM at 47 procedures. Conclusion: CR-ESD even in non-endemic area is associated with high en bloc resection rates, R0 resection rates and acceptable complication profile. Approximately 50 cases of CR-ESD are required to achieve competency. [ABSTRACT FROM AUTHOR]

Introduction: There are limited data available regarding the connection between heavy metal exposure and mortality among hypertension patients. Aim: We intend to establish an interpretable machine learning (ML) model with high efficiency and robustness that monitors mortality based on heavy metal exposure among hypertension patients. Methods: Our datasets were obtained from the US National Health and Nutrition Examination Survey (NHANES, 2013–2018). We developed 5 ML models for mortality prediction among hypertension patients by heavy metal exposure, and tested them by 10 discrimination characteristics. Further, we chose the optimally performing model after parameter adjustment by genetic algorithm (GA) for prediction. Finally, in order to visualize the model's ability to make decisions, we used SHapley Additive exPlanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) algorithm to illustrate the features. The study included 2347 participants in total. Results: A best-performing eXtreme Gradient Boosting (XGB) with GA for mortality prediction among hypertension patients by 13 heavy metals was selected (AUC 0.959; 95% CI 0.953–0.965; accuracy 96.8%). According to sum of SHAP values, cadmium (0.094), cobalt (2.048), lead (1.12), tungsten (0.129) in urine, and lead (2.026), mercury (1.703) in blood positively influenced the model, while barium (− 0.001), molybdenum (− 2.066), antimony (− 0.398), tin (− 0.498), thallium (− 2.297) in urine, and selenium (− 0.842), manganese (− 1.193) in blood negatively influenced the model. Conclusions: Hypertension patients' mortality associated with heavy metal exposure was predicted by an efficient, robust, and interpretable GA-XGB model with SHAP and LIME. Cadmium, cobalt, lead, tungsten in urine, and mercury in blood are positively correlated with mortality, while barium, molybdenum, antimony, tin, thallium in urine, and lead, selenium, manganese in blood is negatively correlated with mortality. [ABSTRACT FROM AUTHOR]

Endoscopic mucosal resection (EMR) is the recommended technique for colon polypectomy for nonpedunculated lesions that are >20 mm in size not requiring excision. Dual-channel EMR (DC-EMR) uses an endoscope with two working channels to facilitate easier submucosal injection, snare resection, and clip closure of polypectomy defects. There is also promising early literature indicating that this endoscopic modality can reduce the overall learning curve present for single-channel colonoscopy EMR. This chapter will describe the steps and techniques required to perform DC-EMR, potential complications, recommended postprocedure surveillance, and future directions. [ABSTRACT FROM AUTHOR]

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In this work, for the first time, the specific impedances of various injection solutions as well as the surface and tissue impedance after injection of these solutions were analyzed and compared regarding the radio-frequency surgical cutting process. The impedances of 0.9% NaCl, 4% gelatine, 6% hydroxyethyl starch, 10% glycerol/5% fructose, 10% glucose, 5% and 20% albumin, blood, and blood plasma as well as aqua destillata have been tested in vitro. Even if EMR and ESD are routinely used in clinical practice, there is so far no easy, fast, and safe method to remove larger lesions en bloc. We show that the impedance of the injected solution shows to be a crucial factor for safe removal, especially of larger lesions (Ø > 20 mm) and more importantly in accordance with the requirements of oncology and pathology. Key messages: Impedance is playing a crucial factor in the radio-frequency (RF)-surgery. With a higher Impedance there will be less current necessary to reach the aimed voltage. Injection solution Aqua destillata and 10% Glucose, show significantly higher Impedances. Higher impedances lead to less surgical related complications. Minor changes in existing method to improve patent safety. [ABSTRACT FROM AUTHOR]

The blockchain-based Electronic Medical Record (EMR) data storage system encounters challenges which are data leakage, insufficient access control, and low retrieval efficiency. In response to these issues, this paper proposes a lightweight searchable encryption and access control system for sharing EMR data securely. The lightweight searchable encryption scheme which is achieved by integrating the trapdoor verification phase with the keyword retrieval phase is constructed using BGG13 + and MP12. User access control is implemented through a Boolean circuit to replace arithmetic operations and thus improve arithmetic efficiency. Since logic operations can reduce the computation time, this paper uses Boolean circuits for user rights verification implementation. In addition, this paper adopts the Bloom filter as the system index to enhance the efficiency of block-chain data retrieval. According to the simulation results, there is a performance advantage of this system over similar systems. [ABSTRACT FROM AUTHOR]

This paper represents a wide incident angle-polarization insensitive, stable in results, and compact-sized metamaterial absorber that can be used for Doppler navigation aids and remote sensing applications in Earth Exploration Satellite Services. The unit cell dimension was subwavelength-sized of 0.112λ X 0.112λ, with a good effective medium ratio (8.9), and achieved polarization insensitivity at a maximum incident angle up to 180°, making it more effective for proposed applications. The absorber resonated at 3.855 GHz, 5.13 GHz, 9.855 GHz, 13.335 GHz, and 16.02 GHz with single negative metamaterial properties due to negative permeability and absorptions of 99.7 %, 99.2 %, 98.6 %, 98.1 %, and 97.9 %, respectively. An RLC equivalent circuit on ADS was analyzed to validate the simulated results using the dipoles created by the surface currents. The absorber is cost-effective as no lumped elements or multilayer substrate materials were used, making fabricating less time-consuming and simple. The simulated results were validated by measuring data from a vector network analyzer after fabricating it. The proposed metamaterial absorber is suitable for use in Doppler navigation and Earth Exploration Satellite Services, and this research can further be extended to beamforming and sensing applications in the future. [Display omitted] • A novel maze-enclosed quad symmetric kite-shaped metamaterial absorber is proposed for quad band applications. • The absorber was designed with subwavelength size of 0.112λ X 0.112λ mm with maximum absorption of 99.7%. • It works perfectly for both co and cross-polarized waves and was justified by simplified equivalent circuit. • Absorptions with SNG features can be used to improve sensing, antenna gain, and EM coupling reduction. • This absorber is ideal for using with Earth Exploration Satellite Services and Doppler Navigation systems. [ABSTRACT FROM AUTHOR]

The study examined the emission of electromagnetic radiation (EMR) from cement/Ba0.06Bi0.47Na0.47TiO3 (BBNT) composites when subjected to drop weight impact loads, aiming to explore their potential as sensors in civil structures. The generation of EMR in this context can be attributed to the increased movement of ions within pores and dipole oscillation along the grain boundaries of BBNT. The increase of BBNT content and impact load cause a noticeable rise in the values of EMR voltage, dominant frequency and the average rate of EMR energy release. Notably, the impact-generated EMR voltage data can be excellently fitted with a 5th-order bivariate polynomial function (adjusted r2 = 0.9353). Furthermore, the EMR voltage exhibits a decreasing pattern when measured at various distances from the sample, until it stabilizes after 12 cm. These findings suggest that the EMR technique holds promise as an effective tool for real-time monitoring of civil structures in situ.

Abstract Background Medical records are a valuable source for understanding patient health conditions. Doctors often use these records to assess health without solely depending on time-consuming and complex examinations. However, these records may not always be directly relevant to a patient’s current health issue. For instance, information about common colds may not be relevant to a more specific health condition. While experienced doctors can effectively navigate through unnecessary details in medical records, this excess information presents a challenge for machine learning models in predicting diseases electronically. To address this, we have developed ‘al-BERT’, a new disease prediction model that leverages the BERT framework. This model is designed to identify crucial information from medical records and use it to predict diseases. ‘al-BERT’ operates on the principle that the structure of sentences in diagnostic records is similar to regular linguistic patterns. However, just as stuttering in speech can introduce ‘noise’ or irrelevant information, similar issues can arise in written records, complicating model training. To overcome this, ‘al-BERT’ incorporates a semi-supervised layer that filters out irrelevant data from patient visitation records. This process aims to refine the data, resulting in more reliable indicators for disease correlations and enhancing the model’s predictive accuracy and utility in medical diagnostics. Method To discern noise diseases within patient records, especially those resembling influenza-like illnesses, our approach employs a customized semi-supervised learning algorithm equipped with a focused attention mechanism. This mechanism is specifically calibrated to enhance the model’s sensitivity to chronic conditions while concurrently distilling salient features from patient records, thereby augmenting the predictive accuracy and utility of the model in clinical settings. We evaluate the performance of al-BERT using real-world health insurance data provided by Taiwan’s National Health Insurance. Result In our study, we evaluated our model against two others: one based on BERT that uses complete disease records, and another variant that includes extra filtering techniques. Our findings show that models incorporating filtering mechanisms typically perform better than those using the entire, unfiltered dataset. Our approach resulted in improved outcomes across several key measures: AUC-ROC (an indicator of a model’s ability to distinguish between classes), precision (the accuracy of positive predictions), recall (the model’s ability to find all relevant cases), and overall accuracy. Most notably, our model showed a 15% improvement in recall compared to the current best-performing method in the field of disease prediction. Conclusion The conducted ablation study affirms the advantages of our attention mechanism and underscores the crucial role of the selection module within al-BERT.

Abstract With the rapid development of modern medical technology and the dramatic increase in the amount of medical data, traditional centralized medical information management is facing many challenges. In recent years blockchain, which is a peer-to-peer distributed database, has been increasingly accepted and adopted by different industries and use cases. Key areas of healthcare blockchain applications include electronic medical record (EMR) management, medical device supply chain management, remote condition monitoring, insurance claims and personal health data (PHD) management, among others. Even so, there are a number of challenges in applying blockchain concepts to healthcare and its data, including interoperability, data security privacy, scalability, TPS and so on. While these challenges may hinder the development of blockchain in healthcare scenarios, they can be improved with existing technologies In this paper, we propose a blockchain-based healthcare operations management framework that is combined with the Interplanetary File System (IPFS) for managing EMRs, protects data privacy through a distributed approach while ensuring that this medical ledger is tamper-proof. Doctors act as full nodes, patients can participate in network maintenance either as light nodes or as full nodes, and the hospital acts as the endpoint database of data, i.e., the IPFS node, which saves the arithmetic power of nodes and allows the data stored in the hospitals and departments to be shared with the other organizations that have uploaded the data. Therefore, the integration of blockchain and zero-knowledge proof proposed in this paper helps to protect data privacy and is efficient, better scalable, and more throughput.

Background and Objectives: Endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD) are both well-established and effective treatments for dysplasia and early cancer in Barrett's esophagus (BE). This study aims to compare the short- and long-term outcomes associated with these procedures in treating Barrett's neoplasia. Materials and Methods: This single-center retrospective cohort study included 95 patients, either EMR (n = 67) or ESD (n = 28), treated for Barrett's neoplasia at Sahlgrenska University Hospital between 2004 and 2019. The primary outcome was the complete (en-bloc) R0 resection rate. Secondary outcomes included the curative resection rate, additional endoscopic resections, adverse events, and overall survival. Results: The complete R0 resection rate was 62.5% for ESD compared to 16% for EMR (p < 0.001). The curative resection rate for ESD was 54% versus 16% for EMR (p < 0.001). During the follow-up, 22 out of 50 patients in the EMR group required additional endoscopic resections (AERs) compared to 3 out of 21 patients in the ESD group (p = 0.028). There were few adverse events associated with both EMR and ESD. In both the stratified Kaplan–Meier survival analysis (Log-rank test, Chi-square = 2.190, df = 1, p = 0.139) and the multivariate Cox proportional hazards model (hazard ratio of 0.988; 95% CI: 0.459 to 2.127; p = 0.975), the treatment group (EMR vs. ESD) did not significantly impact the survival outcomes. Conclusions: Both EMR and ESD are effective and safe treatments for BE neoplasia with few adverse events. ESD resulted in higher curative resection rates with fewer AERs, indicating its potential as a primary treatment modality. However, the survival analysis showed no difference between the methods, highlighting their comparable long-term outcomes. [ABSTRACT FROM AUTHOR]

A Penta band negative permittivity metamaterial using a split disc ring resonator for satellite applications is investigated in this paper. The proposed structure features a double split ring resonator with a split disc resonator attached on top of a high frequency suitable dielectric substrate Rogers RO 4350B (lossy) with a flexible thickness of 0.168 mm. The CST microwave studio 2019 simulator is used to evaluate the performance of the metamaterial structure. At 2.38 GHz (S-band), 6.60 GHz (C-band), 7.32 GHz (C-band), 8.60 GHz (X-band) and 16.34 GHz (Ku-band), the structure offers Penta band resonances of transmission coefficient (S21) with magnitudes of -34.60 dB, -35.39 dB, -30.32 dB, -32.65 dB and − 58.80 dB, respectively. The structure also shows the bandwidths of 0.26, 0.33, 0.24, 0.30 and 3.64 GHz at Penta band resonances. The characteristics of the metamaterial structure are elucidated through the effective medium parameter scenario. To provide additional clarity, electromagnetic field and surface current analysis plots are examined for different resonance frequencies. Negative permittivity has been realized in the frequency ranges of 2.38–3.20 GHz, 6.60–6.86 GHz, 7.32–7.72 GHz, 8.60–9.28 GHz and 16.34–19.76 GHz. The value of the relative permeability has been noticed nearly zero at all resonances. The value of the refractive index has also been perceived negative at all resonances. An effective medium ratio (EMR) of the proposed split disc resonator structure is 10.50 at 2.38 GHz, demonstrating its compactness and efficiency. The ADS software creates an equivalent circuit to verify the CST and HFSS simulator result. Fabrication of the proposed structure was done for experimental validation. The findings demonstrate a close match between simulation results using different simulators and experimental results. Due to its excellent bandwidth and superior EMR, the proposed structure presents a viable option for S, C, X, and Ku satellite bands, as well as for applications requiring antenna gain enhancement. [ABSTRACT FROM AUTHOR]

The Antiretroviral Therapy (ART) management system is a comprehensive software application designed to streamline and enhance the management and monitoring of patients undergoing antiretroviral treatment for HIV/AIDS. The system aims to improve the quality of care provided to ART patients, ensuring accurate treatment initiation, medication dispensing, clinical monitoring, appointment scheduling, adherence monitoring, side effects management, and reporting. By integrating various functionalities, the system enables healthcare providers to efficiently manage patient data, track treatment outcomes, and make informed decisions for optimal patient care. Additionally, the system prioritizes data security and privacy, complying with relevant regulations and employing measures to protect patient confidentiality. Through its integration capabilities, the system fosters interoperability with other healthcare information systems, promoting seamless data exchange and collaboration. Overall, the ART management system serves as a valuable tool in the comprehensive management of ART patients, ultimately contributing to improved health outcomes for individuals living with HIV/AIDS. [ABSTRACT FROM AUTHOR]

With the rapid development of modern medical technology and the dramatic increase in the amount of medical data, traditional centralized medical information management is facing many challenges. In recent years blockchain, which is a peer-to-peer distributed database, has been increasingly accepted and adopted by different industries and use cases. Key areas of healthcare blockchain applications include electronic medical record (EMR) management, medical device supply chain management, remote condition monitoring, insurance claims and personal health data (PHD) management, among others. Even so, there are a number of challenges in applying blockchain concepts to healthcare and its data, including interoperability, data security privacy, scalability, TPS and so on. While these challenges may hinder the development of blockchain in healthcare scenarios, they can be improved with existing technologies In this paper, we propose a blockchain-based healthcare operations management framework that is combined with the Interplanetary File System (IPFS) for managing EMRs, protects data privacy through a distributed approach while ensuring that this medical ledger is tamper-proof. Doctors act as full nodes, patients can participate in network maintenance either as light nodes or as full nodes, and the hospital acts as the endpoint database of data, i.e., the IPFS node, which saves the arithmetic power of nodes and allows the data stored in the hospitals and departments to be shared with the other organizations that have uploaded the data. Therefore, the integration of blockchain and zero-knowledge proof proposed in this paper helps to protect data privacy and is efficient, better scalable, and more throughput. [ABSTRACT FROM AUTHOR]

Background: Medical records are a valuable source for understanding patient health conditions. Doctors often use these records to assess health without solely depending on time-consuming and complex examinations. However, these records may not always be directly relevant to a patient's current health issue. For instance, information about common colds may not be relevant to a more specific health condition. While experienced doctors can effectively navigate through unnecessary details in medical records, this excess information presents a challenge for machine learning models in predicting diseases electronically. To address this, we have developed 'al-BERT', a new disease prediction model that leverages the BERT framework. This model is designed to identify crucial information from medical records and use it to predict diseases. 'al-BERT' operates on the principle that the structure of sentences in diagnostic records is similar to regular linguistic patterns. However, just as stuttering in speech can introduce 'noise' or irrelevant information, similar issues can arise in written records, complicating model training. To overcome this, 'al-BERT' incorporates a semi-supervised layer that filters out irrelevant data from patient visitation records. This process aims to refine the data, resulting in more reliable indicators for disease correlations and enhancing the model's predictive accuracy and utility in medical diagnostics. Method: To discern noise diseases within patient records, especially those resembling influenza-like illnesses, our approach employs a customized semi-supervised learning algorithm equipped with a focused attention mechanism. This mechanism is specifically calibrated to enhance the model's sensitivity to chronic conditions while concurrently distilling salient features from patient records, thereby augmenting the predictive accuracy and utility of the model in clinical settings. We evaluate the performance of al-BERT using real-world health insurance data provided by Taiwan's National Health Insurance. Result: In our study, we evaluated our model against two others: one based on BERT that uses complete disease records, and another variant that includes extra filtering techniques. Our findings show that models incorporating filtering mechanisms typically perform better than those using the entire, unfiltered dataset. Our approach resulted in improved outcomes across several key measures: AUC-ROC (an indicator of a model's ability to distinguish between classes), precision (the accuracy of positive predictions), recall (the model's ability to find all relevant cases), and overall accuracy. Most notably, our model showed a 15% improvement in recall compared to the current best-performing method in the field of disease prediction. Conclusion: The conducted ablation study affirms the advantages of our attention mechanism and underscores the crucial role of the selection module within al-BERT. [ABSTRACT FROM AUTHOR]

Abstract Rationale Short‐term weight loss is possible in a variety of settings. However, long‐term, free‐living weight loss maintenance following structured weight loss interventions remains elusive. Objective The purpose was to study body weight trajectories over 2 years of intensive lifestyle intervention (ILI) and up to 4 years of follow‐up versus usual care (UC). Methods Data were obtained from electronic medical records (EMRs) from participating clinics. Baseline (Day 0) was established as the EMR data point closest but prior to the baseline date of the trial. The sample included 111 ILI and 196 UC patients. The primary statistical analysis focused on differentiating weight loss trajectories between ILI and UC. Results The ILI group experienced significantly greater weight loss compared with the UC group from Day 100 to Day 700, beyond which there were no significant differences. Intensive lifestyle intervention patients who maintained ≥5% and ≥10% weight loss at 24 months demonstrated significantly greater weight loss (p

The dynamism of the application information technology in the health sector, especially in hospitals, which is currently being developed is the electronic medical record (EMR). Global competition in the era of industrial revolution 4.0 makes all hospitals have to be ready for the changes that will occur in the management of medical record management. This study aims to analyze the influence of organizational culture with individual readiness as a mediator on championing behavior in the implementation of electronic medical records (EMR) at Muhammadiyah Hospital. Respondents amounted to 133 people consisting of professional health workers who will later be involved implementation of EMR. The research instrument was in the form of a questionnaire via a google form link. Analysis using SEM (structural equation model) with Lisrel. The results showed that organizational culture significantly affected individual readiness (?=0.67, t-value=7.40). Organizational culture has a significant effect on championing behavior (?=0.42, t-value=4.10). Individual readiness significantly affects championing behavior (?=0.48 , t-value = 4.56). Individual readiness is also a significant mediator of the relationship between organizational culture and championing behavior (complementary mediation type). A strong organizational culture will support the readiness of the organization's planned changes. A strong organizational culture also influences behavior to fight for the success of the change plan. Through individual readiness, organizational culture influences behavior to fight for the successful implementation of EMR. So, organizations need to prepare individuals well for the success of the change plan. Keywords : Championing Behavior, EMR, Organizational Culture, Readiness for Change

Yi Sun,1,2 Hong Wang,3 Minghao Gu,4 Xingyu Zhang,5 Xiudi Han,1, Xuedong Liu,1 1Department of Respiratory and Critical Care Medicine, Qingdao Municipal Hospital Group, Qingdao, Shandong Province, 266000, People’s Republic of China; 2School of Clinical Medicine, Shandong Second Medical University, Weifang, Shandong Province, 261000, People’s Republic of China; 3Hospital-Acquired Infection Control Department, Qingdao Municipal Hospital Group, Qingdao, Shandong Province, 266000, People’s Republic of China; 4School of Medicine, Qingdao University, Qingdao, Shandong Province, 266000, People’s Republic of China; 5Human Resources Department, Qingdao Municipal Hospital Group, Qingdao, Shandong Province, 266000, People’s Republic of ChinaCorrespondence: Xuedong Liu; Xiudi Han, Email xuedongliu0607@163.com; hanxiudi@163.comBackground: Data about eosinophil-to-lymphocyte ratio (ELR) and eosinophil-to-monocyte ratio (EMR) in patients with community-acquired pneumonia (CAP) are rare. We aimed to evaluate the role of EMR and ELR in predicting disease severity and mortality in patients with CAP.Methods: A total of 454 patients (76 with severe CAP (SCAP), 378 with non-SCAP) were enrolled from November 18, 2020, and November 21, 2021. Laboratory examination on day 1 after admission was measured. The ELR and EMR values were calculated for patients. Propensity score matching (PSM) was performed to balance potential confounding factors. Binary logistic regression model was fitted to identify the potential risk factors for disease severity and Cox proportional hazards regression model analysis for mortality in CAP. Receiver operating characteristic (ROC) analysis was performed to distinguish disease severity and mortality.Results: EMR and ELR at admission were significantly lower in SCAP patients than in non-SCAP patients (P< 0.001). EMR < 0.018 ([OR] =  12.104, 95% CI: 4.970– 29.479), neutrophil (NEU) ([OR]=1.098, 95% CI:1.005– 1.199), and age ([OR]=1.091, 95% CI:1.054– 1.130) were independent risk factors for disease severity of CAP. EMR < 0.032 ([HR] =  5.816, 95% CI: 1.704– 9.848) was an independent predictor of in-hospital mortality. Combining EMR or ELR with CRB-65 improved the overall accuracy of disease severity prediction (AUC from 0.894 to 0.937), the same as CURB-65. The area under the curve of EMR (AUC=0.704; 95% CI: 0.582– 0.827) to predict in-hospital mortality was higher than that of CURB-65 (AUC=0.619; 95% CI: 0.484– 0.754). Otherwise, EMR combined with CRB-65 (AUC=0.721; 95% CI: 0.592– 0.851) had significantly higher diagnostic accuracy for in-hospital mortality than that of CURB-65 alone.Conclusion: EMR combined with CRB-65 was superior to CURB-65 in predicting mortality in patients with CAP. This new combination was simpler and easier to obtain for physicians in clinics or admission, and it was more convenient for early recognition of patients with poor prognoses.Keywords: community-acquired pneumonia, EMR, ELR, CURB-65, CRB-65, severity of disease, mortality

Abstract There are limited data available regarding the connection between hypertension and heavy metal exposure. The authors intend to establish an interpretable machine learning (ML) model with high efficiency and robustness that identifies hypertension based on heavy metal exposure. Our datasets were obtained from the US National Health and Nutrition Examination Survey (NHANES, 2013–2020.3). The authors developed 5 ML models for hypertension identification by heavy metal exposure, and tested them by 10 discrimination characteristics. Further, the authors chose the optimally performing model after parameter adjustment by Genetic Algorithm (GA) for identification. Finally, in order to visualize the model's ability to make decisions, the authors used SHapley Additive exPlanation (SHAP) and Local Interpretable Model‐Agnostic Explanations (LIME) algorithm to illustrate the features. The study included 19 368 participants in total. A best‐performing eXtreme Gradient Boosting (XGB) with GA for hypertension identification by 16 heavy metals was selected (AUC: 0.774; 95% CI: 0.772–0.776; accuracy: 87.7%). According to SHAP values, Barium (0.02), Cadmium (0.017), Lead (0.017), Antimony (0.008), Tin (0.007), Manganese (0.006), Thallium (0.004), Tungsten (0.004) in urine, and Lead (0.048), Mercury (0.035), Selenium (0.05), Manganese (0.007) in blood positively influenced the model, while Cadmium (−0.001) in urine negatively influenced the model. Study participants' hypertension associated with heavy metal exposure was identified by an efficient, robust, and interpretable GA‐XGB model with SHAP and LIME. Barium, Cadmium, Lead, Antimony, Tin, Manganese, Thallium, Tungsten in urine, and Lead, Mercury, Selenium, Manganese in blood are positively correlated with hypertension, while Cadmium in blood is negatively correlated with hypertension.

This work explores the influence of a pre-engineered notch on the electromagnetic radiation (EMR) parameters in NiTi shape memory alloy (SMA) during tensile tests. The test data showed that the EMR signal fluctuated between oscillatory and exponential, signifying that the specimen's viscosity damping coefficient changes during strain hardening. The EMR parameters, maximum EMR amplitude, and average EMR energy release rate remained constant initially but rose sharply with the plastic zone radius with progressive loading. It was postulated that new Frank–Read sources permit dislocation multiplication and increase the number of edge dislocations participating in EMR emissions, leading to a rise in the value of EMR parameters. The study of the correlation between EMR emission parameters and the plastic zone radius before the crack tip is a vital crack growth monitoring tool. An analysis of the interrelationship of the EMR energy release rate at fracture with the elastic strain energy release rate would help develop an innovative approach to assess fracture toughness, a critical parameter for the design and safety of metals. The microstructural analysis of tensile fractures and the interrelation between deformation behaviours concerning the EMR parameters offers a novel and real-time approach to improve the extant understanding of the behaviour of metallic materials. [ABSTRACT FROM AUTHOR]

Background: Appendiceal orifice lesions are often managed operatively with limited or oncologic resections. The aim is to report the management of appendiceal orifice mucosal neoplasms using advanced endoscopic interventions. Methods: Patients with appendiceal orifice mucosal neoplasms who underwent advanced endoscopic resections between 2011 and 2021 with either endoscopic mucosal resection (EMR), endoscopic mucosal dissection (ESD), hybrid ESD, or combined endoscopic laparoscopic surgery (CELS) were included from a prospectively collected dataset. Patient and lesion details and procedure outcomes are reported. Results: Out of 1005 lesions resected with advanced endoscopic techniques, 41 patients (4%) underwent appendiceal orifice mucosal neoplasm resection, including 39% by hybrid ESD, 34% by ESD, 15% by EMR, and 12% by CELS. The median age was 65, and 54% were male. The median lesion size was 20 mm. The dissection was completed piecemeal in 49% of patients. Post-procedure, one patient had a complication within 30 days and was admitted with post-polypectomy abdominal pain treated with observation for 2 days with no intervention. Pathology revealed 49% sessile-serrated lesions, 24% tubular adenomas, and 15% tubulovillous adenomas. Patients were followed up for a median of 8 (0–48) months. One patient with a sessile-serrated lesion experienced a recurrence after EMR which was re-resected with EMR. Conclusion: Advanced endoscopic interventions for appendiceal orifice mucosal neoplasms can be performed with a low rate of complications and early recurrence. While conventionally lesions at the appendiceal orifice are often treated with surgical resection, advanced endoscopic interventions are an alternative approach with promising results which allow for cecal preservation. [ABSTRACT FROM AUTHOR]

Background: In recent years, the incidence of gastrointestinal neuroendocrine tumors (GI-NETs) has remarkably increased due to the widespread use of screening gastrointestinal endoscopy. Currently, the most common treatments are surgery and endoscopic resection. Compared to surgery, endoscopic resection possesses a higher risk of resection margin residues for the treatment of GI-NETs. Methods: A total of 315 patients who underwent surgery or endoscopic resection for GI-NETs were included. We analyzed their resection modality (surgery, ESD, EMR), margin status, Preoperative marking and Prognosis. Results: Among 315 patients included, 175 cases underwent endoscopic resection and 140 cases underwent surgical treatment. A total of 43 (43/175, 24.57%) and 10 (10/140, 7.14%) patients exhibited positive resection margins after endoscopic resection and surgery, respectively. Multivariate regression analysis suggested that no preoperative marking and endoscopic treatment methods were risk factors for resection margin residues. Among the patients with positive margin residues after endoscopic resection, 5 patients underwent the radical surgical resection and 1 patient underwent additional ESD resection. The remaining 37 patients had no recurrence during a median follow-up of 36 months. Conclusions: Compared with surgery, endoscopic therapy has a higher margin residual rate. During endoscopic resection, preoperative marking may reduce the rate of lateral margin residues, and endoscopic submucosal dissection may be preferred than endoscopic mucosal resection. Periodical follow-up may be an alternative method for patients with positive margin residues after endoscopic resection. [ABSTRACT FROM AUTHOR]

Summary: Electromagnetic radiation (EMR) has deleterious effects on sperm motility and viability, as well as oocyte membrane and organelle structure. The aim was to assess the effects of cell phone radiation on preimplantation embryo morphokinetics and blastocyst viability in mice. For superovulation, 20 female mice were treated with intraperitoneal (IP) injections of 10 IU pregnant mare's serum gonadotropin (Folligon® PMSG), followed by 10 IU of human chorionic gonadotropin (hCG) after 48 h. The zygotes (n = 150) from the control group were incubated for 4 days. The experimental zygotes (n = 150) were exposed to a cell phone emitting EMR with a frequency range 900–1800 MHz for 30 min on day 1. Then, all embryos were cultured in the time-lapse system and annotated based on time points from the 2-cell stage (t2) to hatched blastocyst (tHDyz), as well as abnormal cleavage patterns. Blastocyst viability was assessed using Hoechst and propidium iodide staining. Significant increases (P < 0.05) were observed in the cleavage division time points of t2, t8, t10, and t12 of the experimental group compared with the controls. In terms of blastocyst formation parameters, a delay in embryo development was observed in the experimental group compared with the controls. Data analysis of the time intervals between the two groups showed a significant difference in the s3 time interval (P < 0.05). Also, the rates of fragmentation, reverse cleavage, vacuole formation, and embryo arrest were significantly higher in the experimental group (P < 0.05). Furthermore, the cell survival rate in the experimental group was lower than the control group (P < 0.05). Exposure to EMR has detrimental consequences for preimplantation embryo development in mice. These effects can manifest as defects in the cleavage stage and impaired blastocyst formation, leading to lower cell viability. [ABSTRACT FROM AUTHOR]

Copepods belonging to planktonic species are small crustaceans found in water bodies. Plankton are the primary producers that are important for food webs and ecosystems. This study analyzes the effects of planktonic species in current telecommunication devices that emit radio frequency and produce EM fields. In recent years, there has been massive growth in the number of mobile tower stations. Case studies on the effects of radiation from these towers have been carried out in various organisms. In the present study, plankton species were exposed to two EMFsof 190V and 230V and an RF of 9GHz for different time durations. The high mortality percentage of calanoid copepod Neodiaptomus species was 21.81±3.14, 34.55±1.81, and cyclopoid copepod Mesocyclops species was 18.18±3.15, 21.21±2.78 190v and 230v power supplies exposed at 300 min, respectively. Variation in the amount of protein in Neodiaptomus sp. and Mesocyclops sp. was indicated by the effect of radiation. Data on mortality, sublethal duration, motility, protein concentration, and amino acid content are discussed in the present study. [ABSTRACT FROM AUTHOR]

Endoscopic submucosa dissection (ESD) allows complete excision of the whole lesion, which results in a higher percentage of complete excision and an improved quality of life by minimizing the amount of excision as opposed to an endoscopic mucosal resection (EMR). Although ESD is now being carried out in the majority of hospitals, ESD's possible complications (such as trauma and perforation) have given rise to doubts about ESD practices in patients with early‐stage stomach cancer when deciding on therapy and reimbursement. This study was designed to evaluate the effectiveness and safety of ESD over EMR in treating early‐stage stomach cancer. Four main databases have been searched, including EMBASE and published. The ROBINS‐I tool suggested in the Cochrane Handbook has been applied to evaluate the quality of the chosen trials. It may better reflect the risk of bias in the included studies. The meta‐analyses were carried out with ReMan 5.3, and the results were treated with endote. Seven cohort studies have been completed. Meta analysis indicated that EMR and ESD surgery did not differ significantly from each other in terms of postoperative haemorrhage (OR, 0.76; 95%CI, 0.56,1.04 p = 0.09); EMR, however, was associated with a lower rate of postoperative perforation than ESD surgery (OR, 0.36; 95%CI, 0.24,0.54 p < 0.0001). Taking into account that ESD and EMR did not differ significantly in the risk of wound bleeding, even though the risk of perforation is not likely to result in life‐threatening illness. In the analysis of these data, however, the potential advantages of EMR might be greater than ESD. [ABSTRACT FROM AUTHOR]

Workload in the emergency department (ED) fluctuates and there is no established model for measurement of clinician-level ED workload. The aim of this study was to measure perceived ED workload and assess the relationship between perceived workload and objective measures of workload from the electronic medical record (EMR). This study was conducted at a tertiary care, academic ED from July 1, 2020 through April 13, 2021. Attending workload perceptions were collected using a 5-point scale in three care areas with variable acuity. We collected eight EMR measures thought to correlate with perceived workload. EMR values were compared across areas of the department using ANOVA and correlated with attending workload ratings using linear regression. We collected 315 unique workload ratings, which were normally distributed. For the entire department, there was a weak positive correlation between reported workload perception and mean percentage of inpatient admissions (r = 0.23; p < 0.001), intensive care unit admissions (r = 0.2; p < 0.001), patient arrivals per shift (r = 0.14; p = 0.017), critical care billed visits (r = 0.22; p < 0.001), cardiopulmonary resuscitation code activations (r = 0.2; p < 0.001), and level 5 visits (r = 0.13; p = 0.02). There was weak negative correlation for ED discharges (r = –0.23; p < 0.001). Several correlations were stronger in individual care areas, including percent admissions in the lowest-acuity area (r = 0.43; p = 0.033) and patient arrivals in the highest-acuity area (r = 0.44; p <.01). No significant correlation was found in any area for observation admissions or trauma activations. In this study, EMR measures of workload were not closely correlated with ED attending physician workload perception. Future study should examine additional factors contributing to physician workload outside of the EMR. [ABSTRACT FROM AUTHOR]

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Objective. This study aimed to investigate allied health professionals' (AHPs') perspectives preand post-implementation of an electronic medical record (EMR) in a tertiary health service in Australia and examine factors influencing user acceptance. Methods. Data were collected preand post-EMR implementation via cross-sectional online surveys based on the Unified Theory of Acceptance and Usage of Technology (UTAUT). All AHPs at a large tertiary hospital were invited to complete the surveys. Data analysis included descriptive analysis, Mann--Whitney U tests for pre-post item- and construct-level comparison and content analysis of free-text responses. The theoretical model was empirically tested using partial least squares structural equation modelling. Results. AHPs had positive attitudes toward EMR use both pre- and post-implementation. Compared to pre-implementation, AHPs felt more positive post-implementation about system ease of use and demonstrated decreased anxiety and apprehension regarding EMR use. AHPs felt they had adequate resources and knowledge to use EMR and reported real-time data accessibility as a main advantage. Disadvantages of EMR included an unfriendly user interface, system outages and decreased efficiency. Conclusions. As AHPs increase EMR system familiarity, their positivity towards its use increases. An understanding of what influences AHPs when implementing new compulsory technology can inform change management strategies to improve adoption. [ABSTRACT FROM AUTHOR]

Effective monitoring and early warning methods are crucial for enhancing safety and sustainability in deep coal resource extraction, particularly in mitigating rock burst disasters triggered by abrupt rock failure under high–ground–stress conditions. This paper presents the results of experimental investigations that involved conventional uniaxial direct and graded mechanical tests on granite that concurrently collected acoustic emission (AE) and electromagnetic radiation (EMR) signals. This study focused on the temporal evolution patterns of characteristic parameters in AE and EMR signals during granite deformation and fracture processes. To deconstruct and understand these temporal evolution characteristics, multifractal and critical slowing–down theories are introduced. The research findings reveal significant correlations between the evolution of AE and EMR characteristic parameters and the stages of rock deformation and fracture. Notably, dynamic changes in multifractal parameters (Δα and Δf) quantitatively reflected the deformation and fracture processes, with abrupt increases in Δα and sudden decreases in Δf closely associated with large–scale rock fractures. The temporal continuity of critical slowing–down parameters (variance and autocorrelation coefficient) demonstrated increased sensitivity as rock destruction approaches, with the variance emerging as a crucial indicator for large–scale fractures. This study observed a sudden increase in the variance of AE and EMR signals when the stress level reached 80–90% of the peak stress. Joint monitoring through diverse methods and multiple indicators enhanced the effectiveness of rock burst disaster warnings, contributing to the safety and sustainability of coal resource extraction. Further refinement and exploration of these indicators offer promising avenues for advancing rock failure monitoring and early warning capabilities in coal mines. [ABSTRACT FROM AUTHOR]

There are limited data available regarding the connection between hypertension and heavy metal exposure. The authors intend to establish an interpretable machine learning (ML) model with high efficiency and robustness that identifies hypertension based on heavy metal exposure. Our datasets were obtained from the US National Health and Nutrition Examination Survey (NHANES, 2013–2020.3). The authors developed 5 ML models for hypertension identification by heavy metal exposure, and tested them by 10 discrimination characteristics. Further, the authors chose the optimally performing model after parameter adjustment by Genetic Algorithm (GA) for identification. Finally, in order to visualize the model's ability to make decisions, the authors used SHapley Additive exPlanation (SHAP) and Local Interpretable Model‐Agnostic Explanations (LIME) algorithm to illustrate the features. The study included 19 368 participants in total. A best‐performing eXtreme Gradient Boosting (XGB) with GA for hypertension identification by 16 heavy metals was selected (AUC: 0.774; 95% CI: 0.772–0.776; accuracy: 87.7%). According to SHAP values, Barium (0.02), Cadmium (0.017), Lead (0.017), Antimony (0.008), Tin (0.007), Manganese (0.006), Thallium (0.004), Tungsten (0.004) in urine, and Lead (0.048), Mercury (0.035), Selenium (0.05), Manganese (0.007) in blood positively influenced the model, while Cadmium (−0.001) in urine negatively influenced the model. Study participants' hypertension associated with heavy metal exposure was identified by an efficient, robust, and interpretable GA‐XGB model with SHAP and LIME. Barium, Cadmium, Lead, Antimony, Tin, Manganese, Thallium, Tungsten in urine, and Lead, Mercury, Selenium, Manganese in blood are positively correlated with hypertension, while Cadmium in blood is negatively correlated with hypertension. [ABSTRACT FROM AUTHOR]

Linear mixed models are widely used for analyzing longitudinal datasets, and the inference for variance component parameters relies on the bootstrap method. However, health systems and technology companies routinely generate massive longitudinal datasets that make the traditional bootstrap method infeasible. To solve this problem, we extend the highly scalable bag of little bootstraps method for independent data to longitudinal data and develop a highly efficient Julia package MixedModelsBLB.jl. Simulation experiments and real data analysis demonstrate the favorable statistical performance and computational advantages of our method compared to the traditional bootstrap method. For the statistical inference of variance components, it achieves 200 times speedup on the scale of 1 million subjects (20 million total observations), and is the only currently available tool that can handle more than 10 million subjects (200 million total observations) using desktop computers.

The paper discusses experimental research to analyze how the notch-width ratio (2a/w) impacts Electromagnetic Radiation (EMR) emission parameters at tensile fracture in C35000 brass. The EMR emission signals during tensile fracture were captured using a copper chip antenna and stored in an oscilloscope for further analysis. The EMR parameters and mechanical parameters at fracture showed a smooth correlation. Investigating the association between the EMR parameters and the plastic zone radius formed before the crack tip may help develop an innovative tool for crack growth monitoring. The interrelation between the EMR energy release rate and the Elastic strain energy release rate may help create an innovative method for assessing fracture toughness, a fundamental property of metallic materials. The EMR energy release rate exhibited a parabolic relationship with an analytical correlation of stacking fault energy. Field emission scanning electron microscopy (FESEM) examined the fractured specimen's microstructure. A thorough examination of the relationship between dislocations, EMR characteristics, and real-time applications could be a novel technique for understanding material behaviour in detail.