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The adoption of artificial intelligence (AI) in healthcare is growing rapidly. Remote patient monitoring (RPM) is one of the common healthcare applications that assist doctors to monitor patients with chronic or acute illness at remote locations, elderly people in‐home care, and even hospitalized patients. The reliability of manual patient monitoring systems depends on staff time management which is dependent on their workload. Conventional patient monitoring involves invasive approaches which require skin contact to monitor health status. This study aims to do a comprehensive review of RPM systems including adopted advanced technologies, AI impact on RPM, challenges and trends in AI‐enabled RPM. This review explores the benefits and challenges of patient‐centric RPM architectures enabled with Internet of Things wearable devices and sensors using the cloud, fog, edge, and blockchain technologies. The role of AI in RPM ranges from physical activity classification to chronic disease monitoring and vital signs monitoring in emergency settings. This review results show that AI‐enabled RPM architectures have transformed healthcare monitoring applications because of their ability to detect early deterioration in patients' health, personalize individual patient health parameter monitoring using federated learning, and learn human behavior patterns using techniques such as reinforcement learning. This review discusses the challenges and trends to adopt AI to RPM systems and implementation issues. The future directions of AI in RPM applications are analyzed based on the challenges and trends. This article is categorized under:Application Areas > Health CareTechnologies > Artificial IntelligenceTechnologies > Internet of Things [ABSTRACT FROM AUTHOR]

Diabetic kidney disease (DKD) is a complication of diabetes, which is the most common cause of end-stage renal disease (dialysis). DKD has a high mortality rate, and only early detection can nip this disease in the bud. Advanced glycation end products (AGEs)are generally believed to be involved in the occurrence of DKD. Studies have shown that the lens AGEs fluorescence for noninvasive detection has high consistency with the gold standard OGTT, has high sensitivity and specificity, and could be used as a practical tool for the early screening of type 2 diabetes mellitus (T2DM).Therefore, we speculated that the noninvasive lens AGEs fluorescence detection method can be used to predict the occurrence of DKD. This study detected levels of AGEs in multiple cellular and tissues and analyzed the relationships between AGEs and lens, eyeballs, peripheral blood mononuclear cell (PBMC), serum, and kidney. Additionally, we examined the possible role of lens AGEs fluorescence in DKD screening. Our preexperimental study found that lens AGE levels in patients with T2DM were positively correlated with PBM and serum AGE levels. Lens AGE levels in patients with T2DM were negatively correlated with eGFR and positively correlated with urinary ACR. The animal and cell experiments showed that the AGE levels in the eyeballs of DM mice were also positively correlated with those in the serum and kidney. To increase the reliability of the experiment, we increased the sample size. In our results, lens AGEs levels were positively correlated with the occurrence of DKD, and the incidence of DKD in the high lens AGEs group was 2.739 times that in the low lens AGEs group. The receiver operating characteristic (ROC) curves showed that patients with T2DM with a lens AGEs value ≥ 0.306 were likely to have DKD. The area under the ROC curve of the noninvasive technique for identifying DKD was 0.757 (95% Cl: 0.677-0.838, p<0.001), and the sensitivity and specificity were 70.0% and 78.7%, respectively. These results suggest that noninvasive lens AGEs detection technology has certain clinical value in diagnosing whether patients with T2DM have DKD. [ABSTRACT FROM AUTHOR]

Diabetic kidney disease (DKD) is a complication of diabetes, which is the most common cause of end-stage renal disease (dialysis). DKD has a high mortality rate, and only early detection can nip this disease in the bud. Advanced glycation end products (AGEs)are generally believed to be involved in the occurrence of DKD. Studies have shown that the lens AGEs fluorescence for noninvasive detection has high consistency with the gold standard OGTT, has high sensitivity and specificity, and could be used as a practical tool for the early screening of type 2 diabetes mellitus (T2DM).Therefore, we speculated that the noninvasive lens AGEs fluorescence detection method can be used to predict the occurrence of DKD. This study detected levels of AGEs in multiple cellular and tissues and analyzed the relationships between AGEs and lens, eyeballs, peripheral blood mononuclear cell (PBMC), serum, and kidney. Additionally, we examined the possible role of lens AGEs fluorescence in DKD screening. Our preexperimental study found that lens AGE levels in patients with T2DM were positively correlated with PBM and serum AGE levels. Lens AGE levels in patients with T2DM were negatively correlated with eGFR and positively correlated with urinary ACR. The animal and cell experiments showed that the AGE levels in the eyeballs of DM mice were also positively correlated with those in the serum and kidney. To increase the reliability of the experiment, we increased the sample size. In our results, lens AGEs levels were positively correlated with the occurrence of DKD, and the incidence of DKD in the high lens AGEs group was 2.739 times that in the low lens AGEs group. The receiver operating characteristic (ROC) curves showed that patients with T2DM with a lens AGEs value ≥ 0.306 were likely to have DKD. The area under the ROC curve of the noninvasive technique for identifying DKD was 0.757 (95% Cl: 0.677-0.838, p

Purpose: To investigate changes in retinal oximetry and the diameter of retinal vasculature in patients with chronic kidney disease (CKD) and relationships between retinal vasculature and the estimated glomerular filtration rate (eGFR), provide a scientific basis for the early detection and diagnosis of CKD. Methods: Eighty‐three patients with CKD and 103 healthy individuals were included after providing informed consent. All participants were examined using a noninvasive technology (Oxymap Inc., Reykjavik, Iceland) for measuring the arterial (SaO2) and venous (SvO2) oxygen saturation and the arteriovenous difference in oxygen saturation (Sa‐vO2). The corresponding retinal vessel diameters of these arterioles (D‐A) and venules (D‐V) were measured. The eGFR of patients with CKD was calculated from the serum creatinine concentration. Results: In general, patients with CKD had higher mean SaO2 values than healthy individuals (100.15 ± 4.68% versus 97.14 ± 4.22%; p < 0.001, mean ± SD). The mean SaO2 in the superior temporal, superior nasal and inferior nasal quadrants significantly increased. There was no significant difference measured in the SvO2 when patients with CKD (63.66 ± 5.29%) and healthy individuals (62.70 ± 5.27%) were compared. The mean Sa‐vO2 of the CKD group (36.49 ± 4.98%) was increased compared with normal subjects (34.44 ± 4.76%) (p = 0.005). The retinal arteriole diameter was narrower in patients with CKD than in normal individuals (117.53 ± 14.88 μm versus 126.87 ± 14.98 μm; p < 0.001, mean ± SD), and the arteriovenous ratio was smaller than in normal individuals (0.71 ± 0.09 versus 0.77 ± 0.09; p < 0.001, mean ± SD). Pearson's two‐tailed correlation showed a significant correlation between the SaO2 and eGFR (R = −0.363, p = 0.001), and narrower retinal arterial calibre was significantly associated with a lower eGFR (R = 0.415, p < 0.001). Conclusion: Based on our results, there were alterations in retinal oxygen saturation and vascular diameter in patients with CKD. Further studies are needed to determine whether such changes play a role in the development of CKD. [ABSTRACT FROM AUTHOR]

In the last two decades, food scientists have attempted to develop new technologies that can improve the detection of insect infestation in fruits and vegetables under postharvest conditions using a multitude of non-destructive technologies. While consumers’ expectations for higher nutritive and sensorial value of fresh produce has increased over time, they have also become more critical on using insecticides or synthetic chemicals to preserve food quality from insects’ attacks or enhance the quality attributes of minimally processed fresh produce. In addition, the increasingly stringent quarantine measures by regulatory agencies for commercial import–export of fresh produce needs more reliable technologies for quickly detecting insect infestation in fruits and vegetables before their commercialization. For these reasons, the food industry investigates alternative and non-destructive means to improve food quality. Several studies have been conducted on the development of rapid, accurate, and reliable insect infestation monitoring systems to replace invasive and subjective methods that are often inefficient. There are still major limitations to the effective in-field, as well as postharvest on-line, monitoring applications. This review presents a general overview of current non-destructive techniques for the detection of insect damage in fruits and vegetables and discusses basic principles and applications. The paper also elaborates on the specific post-harvest fruit infestation detection methods, which include principles, protocols, specific application examples, merits, and limitations. The methods reviewed include those based on spectroscopy, imaging, acoustic sensing, and chemical interactions, with greater emphasis on the noninvasive methods. This review also discusses the current research gaps as well as the future research directions for non-destructive methods’ application in the detection and classification of insect infestation in fruits and vegetables.

Background: Novel non-invasive technologies augment information available to a clinician to enhance diagnosis. Electrical impedance spectroscopy (EIS) is a highly sensitive technology used before biopsy to differentiate equivocal lesions through differences in electrical resistance of benign versus malignant cells. A recent study of an EIS device approved by the United States Food and Drug Administration supported this device's impact on clinical management among dermatology residents. The device provides an EIS score, which increases with greater likelihood of malignancy., Objective: We investigated whether the addition of an EIS score improved uniformity and diagnostic accuracy of pigmented lesions., Methods: A post-hoc analysis of previously collected data from a survey of 164 dermatology residents was performed. Residents were asked to determine whether they would biopsy a lesion based on clinical morphology alone versus clinical morphology with an EIS score. A total of 45 lesions were assessed (including 17 malignant and 28 benign lesions). Subjects were grouped by percent correct pre-EIS score biopsy decisions and divided into quartiles., Results: With clinical assessment alone, the mean correct decisions to biopsy was 59.9%. With the addition of EIS score, the mean increased to 71.0%. All quartiles significantly increased their correct biopsy decisions with EIS ( P <0.001), but the lowest scoring quartiles improved more than the highest scoring quartiles., Conclusion: The data from the EIS device were designed to be integrated into the biopsy decision as an additional piece of information in the diagnostic pathway. The study findings are consistent with this objective. In addition to clinical judgment, the use of the EIS score most increased the lowest-scoring residents, but all were improved after integrating the EIS score. EIS information improved homogeneity of ability and diagnostic accuracy., Competing Interests: DISCLOSURES: Dr. Litchman is a fellow of the National Society for Cutaneous Medicine, which receives grants from Scibase. The other authors report no conflicts of interest relevant to the content of this article., (Copyright © 2021. Matrix Medical Communications. All rights reserved.)

In the last two decades, food scientists have attempted to develop new technologies that can improve the detection of insect infestation in fruits and vegetables under postharvest conditions using a multitude of non-destructive technologies. While consumers' expectations for higher nutritive and sensorial value of fresh produce has increased over time, they have also become more critical on using insecticides or synthetic chemicals to preserve food quality from insects' attacks or enhance the quality attributes of minimally processed fresh produce. In addition, the increasingly stringent quarantine measures by regulatory agencies for commercial import–export of fresh produce needs more reliable technologies for quickly detecting insect infestation in fruits and vegetables before their commercialization. For these reasons, the food industry investigates alternative and non-destructive means to improve food quality. Several studies have been conducted on the development of rapid, accurate, and reliable insect infestation monitoring systems to replace invasive and subjective methods that are often inefficient. There are still major limitations to the effective in-field, as well as postharvest on-line, monitoring applications. This review presents a general overview of current non-destructive techniques for the detection of insect damage in fruits and vegetables and discusses basic principles and applications. The paper also elaborates on the specific post-harvest fruit infestation detection methods, which include principles, protocols, specific application examples, merits, and limitations. The methods reviewed include those based on spectroscopy, imaging, acoustic sensing, and chemical interactions, with greater emphasis on the noninvasive methods. This review also discusses the current research gaps as well as the future research directions for non-destructive methods' application in the detection and classification of insect infestation in fruits and vegetables. [ABSTRACT FROM AUTHOR]