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Introduction: The current ultrasound scan classification system for thyroid nodules is time-consuming, labor-intensive, and subjective. Artificial intelligence (AI) has been shown to increase the accuracy of predicting the malignancy rate of thyroid nodules. This study aims to demonstrate the state-of-the-art Swin Transformer to classify thyroid nodules., Materials and Methods: Ultrasound images were collected prospectively from patients who received fine needle aspiration biopsy for thyroid nodules from January 2016 to June 2021. One hundred thirty-nine patients with malignant thyroid nodules were enrolled, while 235 patients with benign nodules served as controls. Images were fed to Swin-T and ResNeSt50 models to classify the thyroid nodules., Results: Patients with malignant nodules were younger and more likely male compared to those with benign nodules. The average sensitivity and specificity of Swin-T were 82.46% and 84.29%, respectively. The average sensitivity and specificity of ResNeSt50 were 72.51% and 77.14%, respectively. Receiver operating characteristics analysis revealed that the area under the curve of Swin-T was higher (AUC=0.91) than that of ResNeSt50 (AUC=0.82). The McNemar test evaluating the performance of these models showed that Swin-T had significantly better performance than ResNeSt50.Swin-T classifier can be a useful tool in helping shared decision-making between physicians and patients with thyroid nodules, particularly in those with high-risk characteristics of sonographic patterns., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

There are many published cup anteversion measurements for postoperative total hip arthroplasty (THA), including Liaw’s, Lewinnek’s, and Murray’s methods. However, most measurements ignore the potential pelvic rotation on radiographs except in Liaw’s method. Without considering pelvic rotation, clinicians can miscalculate cup anteversion. Therefore, we aimed to quantify the mean degree of pelvic rotation. Herein, we collected 388 radiographs of 98 postoperative THA hips of 77 patients and measured pelvic rotation by measuring h, the horizontal displacement of the sacrococcygeal junction associated with the upper pole of the symphysis pubis, and ssd, the distance between the sacrococcygeal junction and pubic symphysis. The angle θ of pelvic rotation was defined as θ = arc sin (h/ssd) × (180°/π). The mean degree of pelvic rotation was then calculated. The standard deviation of h was 7.84 mm, and the mean ssd was 158 mm. The potential pelvic rotation was 2.50°. The p-values from the paired t-test were all >0.05 when interobserver and intraobserver errors were assessed. This is the first study to quantify the potential pelvic rotation in the coronal plane on postoperative plain radiographs. The potential pelvic rotation was too large to be neglected during the measurement of cup anteversion., Competing Interests: The authors declare no conflicts of interest.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic can be effectively controlled by rapid and accurate identification of SARS-CoV-2-infected cases through large-scale screening. Hypercube pooling polymerase chain reaction (PCR) is frequently used as a pooling technique because of its high speed and efficiency. We attempted to implement the hypercube pooling strategy and found it had a large quantization effect. This raised two questions: is hypercube pooling with edge = 3 actually the optimal strategy? If not, what is the best edge and dimension? We used a C++ program to calculate the expected number of PCR tests per patient for different values of prevalence, edge, and dimension. The results showed that every edge had a best performance range. Then, using C++ again, we created a program to calculate the optimal edge and dimension required for pooling samples when entering prevalence into our program. Our program will be provided as freeware in the hope that it can help governments fight the SARS-CoV-2 pandemic., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wu, Liao, Fuh, Weng, Wang, Chen, Huang, Chen, Chu, Chen, Yeh, Yu, Wu, Lin, Liou, Wu and Liaw.)

Distal radius orientation is important in evaluating Colles' fracture. In most cases, the wrist was protected by a bandage, splint, or cast. Therefore, it was difficult for the radiology technician to take perfect anteroposterior and lateral view radiographs. In this study, we build a mathematical model and calculate the pronation angle needed to produce dorsal tilt, which is a volar tilt in a perfect lateral view radiograph. The formulas are all incorporated into Excel to facilitate usage., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2022 Chen, Wu, Liao, Fuh, Chen, Weng, Wang, Chen, Huang, Chen, Chu, Yeh, Yu, Wu, Lin, Liou, Wu and Liaw.)

The aim of this study is to develop an AI model that accurately identifies referable blepharoptosis automatically and to compare the AI model's performance to a group of non-ophthalmic physicians. In total, 1000 retrospective single-eye images from tertiary oculoplastic clinics were labeled by three oculoplastic surgeons as having either ptosis, including true and pseudoptosis, or a healthy eyelid. A convolutional neural network (CNN) was trained for binary classification. The same dataset was used in testing three non-ophthalmic physicians. The CNN model achieved a sensitivity of 92% and a specificity of 88%, compared with the non-ophthalmic physician group, which achieved a mean sensitivity of 72% and a mean specificity of 82.67%. The AI model showed better performance than the non-ophthalmic physician group in identifying referable blepharoptosis, including true and pseudoptosis, correctly. Therefore, artificial intelligence-aided tools have the potential to assist in the diagnosis and referral of blepharoptosis for general practitioners.

Purpose: Blepharoptosis is a known cause of reversible vision loss. Accurate assessment can be difficult, especially amongst non-specialists. Existing automated techniques disrupt clinical workflow by requiring user input, or placement of reference markers. Neural networks are known to be effective in image classification tasks. We aim to develop an algorithm that can accurately identify blepharoptosis from a clinical photo., Methods: A total of 500 clinical photographs from patients with and without blepharoptosis were sourced from a tertiary ophthalmic center in Taiwan. Images were labeled by two oculoplastic surgeons, with an independent third oculoplastic surgeon to adjudicate disagreements. These images were used to train a series of convolutional neural networks (CNNs) to ascertain the best CNN architecture for this particular task., Results: Of the models that trained on the dataset, most were able to identify ptosis images with reasonable accuracy. We found the best performing model to use the DenseNet121 architecture without pre-training which achieved a sensitivity of 90.1 % with a specificity of 82.4 %, compared to the worst performing model which was used a Resnet34 architecture with pre-training, achieving a sensitivity of 74.1 %, and specificity of 63.6 %. Models with and without pre-training performed similarly (mean accuracy 82.6 % vs. 85.8 % respectively, p = 0.06), though models with pre-training took less time to train (1-minute vs. 16 min, p < 0.01)., Conclusions: We report the use of AI to accurately diagnose blepharoptosis from a clinical photograph with no external reference markers or user input requirement. Most current-generation CNN architectures performed reasonably on this task, with the DenseNet121, and Resnet18 architectures without pre-training performing best in our dataset., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Mismatch of intramedullary nails with the bowing of femur is a frequent clinical finding. Previous studies showed inconsistent results., Methods: We present an algorithm of region growing territory method to get the radii of the anterior bowing of femur. We also tested it on ten radiographs. Plain radiographs of the lateral view of femur from five men and five women taken between January and August 2014 in Taipei Hospital were chosen randomly. The curvature of femur outline and medullary canal were measured for three times each. Radii of curvature of whole femur, proximal, middle and distal parts were calculated and analyzed., Results: The coefficient of variation of the 240 measurements ranged from 0.007 to 0.295 and averaged 0.088. The average radii of curvature of the whole, proximal, middle, and distal femur were 1318 mm, 752 mm, 1379 mm, and 599 mm, respectively. At the distal part of the femur, the radius of curvature of the femur outline (452 mm) was smaller than the medullary canal (746 mm) (p < 0.05). Women's femur was straighter than men's when we compared the whole length (1435 mm vs. 1201 mm, p < 0.05). The radii we calculated were smaller than the current intramedullary nails., Conclusion: The results showed that the inter-observer and intra-observer differences are acceptable, support the impression that different bowing conditions existed for Asians as compared to Caucasians, and also indicate the mismatch of current instruments to the curvature of femur., Competing Interests: The authors declare no conflict of interest.

Purpose: To survey adenoid cystic carcinoma of lacrimal glands in Asian population and investigate the predictability in prognosis following the 8 th edition American Joint Committee on Cancer (AJCC) staging guideline., Study Design: Retrospective study., Methods: The clinical entities and surgical outcomes of the patients who were histologically confirmed with a diagnosis of lacrimal adenoid cystic carcinoma in National Taiwan University Hospital between January 1995 and December 2015 were retrospectively reviewed., Results: Enrolled were 11 patients. The median follow-up was 7.2 years. Eight patients (72.7%) were diagnosed as T1 or T2 disease, and three patients (27.3%) were diagnosed as T3 or T4 disease according to the AJCC 8 th edition guideline. Eye-sparing surgery with radiotherapy was performed in nine patients. Local recurrence was noted in six patients (54.5%) with median disease-free interval of 23.5 months. Six patients (54.5%) developed distant metastases, including lung, bone, and cranial invasions. Overall survival rate during the study period was 54.6%. Five-year overall survival was 81.8% and ten-year overall survival was 68.2%. The Log-rank test for overall survival and disease-free survival between patients with less than T3 disease (p=0.001) and patients with T3 or T4 disease (p=0.006) revealed significant differences., Conclusion: This study highlighted the aggressive nature of adenoid cystic carcinoma of lacrimal glands. Eye-sparing surgery with adjunctive radiotherapy may achieve relatively optimal disease control in diseases staged T1 or T2, but in advanced disease metastasis and mortality are usually inevitable.

Evaluating three-dimensional angle error is necessary because we cannot get every patient's CT or MRI at all times. Creating a method that can calculate angle error from plain radiographs is therefore important. Using vector and trigonometric mathematics, we gradually deduct our formula which can calculate angle error from goal angles (the angles we plan to achieve before operation) to result angles (the angles we get after operation) by two perpendicular radiographs. We also encode it into Micorsoft Excel (Redmond Campus, Redmond, Washington, U.S.) so that it becomes more user-friendly. We hope this tool can be used when evaluating TKR, corrective osteotomy, fracture fixation, and so on., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Many biological networks are signed molecular networks which consist of positive and negative links. To reveal the distinct features between links with different signs, we proposed signed link-clustering coefficients that assess the similarity of inter-action profiles between linked molecules. We found that positive links tended to cluster together, while negative links usually behaved like bridges between positive clusters. Positive links with higher adhesiveness tended to share protein domains, be associated with protein-protein interactions and make intra-connections within protein complexes. Negative links that were more bridge-like tended to make interconnections between protein complexes. Utilizing the proposed measures to group positive links, we observed hierarchical modules that could be well characterized by functional annotations or known protein complexes. Our results imply that the proposed sign-specific measures can help reveal the network structural characteristics and the embedded biological contexts of signed links, as well as the functional organization of signed molecular networks.

Background: Previous work by our group to address the problem of acetabular positioning based on 2D methods resulted in the development of a measurement method with better precision--Liaw's version. This method may help the early diagnosis of acetabular loosening. In the present study, we hypothesized that our computerized ellipse method could improve the precision of measuring acetabular version., Methods: We developed our Elliversion software to measure acetabular version. Using total hip replacement (THR) Simulator, 96 radiographs were synthesized with random femoral inclination and 5° to 52° version, half with the femoral head included and half without. These synthetic radiographs and 28 real radiographs were measured with both Elliversion and the trigonometric method twice by one of the authors with a one-week interval between measurements. We then calculated the difference in the repeated measurements. Student's t-test was used for statistical analysis of the measuring error and inter-measurement difference., Results: In the precision study, for synthetic radiographs including the femoral head, the ellipse method was significantly better than the trigonometric method (p < 0.01). For synthetic radiographs without the femoral head, there was no significant difference between the ellipse method and the trigonometric method (p = 0.19). As for the repeated measurements, for synthetic radiographs including the femoral head, the ellipse method was significantly better than the trigonometric method (p = 0.001), whereas for synthetic radiographs without the femoral head, there was no significant difference between the two methods (p = 0.17). For real radiographs, there was no significant difference between the two measuring methods (p = 0.12). However, if we excluded the four poor-quality radiographs, there was a significant difference between the two measuring methods (p = 0.04)., Discussion: We developed a computerized ellipse method for measuring acetabular version on synthetic radiographs and good-quality real radiographs. This method is characterized by its superior precision as compared to the trigonometric method. With the 2D standardized method (Liaw's version), improving the precision of measurement will help earlier diagnosis of acetabular loosening.

Health examinations can obtain relatively complete health information and thus are important for the personal and public health management. For clinicians, one of the most important works in the health examinations is to interpret the health examination results. Continuously interpreting numerous health examination results of healthcare receivers is tedious and error-prone. This paper proposes a clinical decision support system to assist solving above problems. In order to customize the clinical decision support system intuitively and flexibly, this paper also proposes the rule syntax to implement computer-interpretable logic for health examinations. It is our purpose in this paper to describe the methodology of the proposed clinical decision support system. The evaluation was performed by the implementation and execution of decision rules on health examination results and a survey on clinical decision support system users. It reveals the efficiency and user satisfaction of proposed clinical decision support system. Positive impact of clinical data interpretation is also noted.

In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting data representations are typically high-dimensional and assume diverse forms. Hence, finding a way of transforming them into a unified space of lower dimension generally facilitates the underlying tasks such as object recognition or clustering. To this end, the proposed approach (termed MKL-DR) generalizes the framework of multiple kernel learning for dimensionality reduction, and distinguishes itself with the following three main contributions: first, our method provides the convenience of using diverse image descriptors to describe useful characteristics of various aspects about the underlying data. Second, it extends a broad set of existing dimensionality reduction techniques to consider multiple kernel learning, and consequently improves their effectiveness. Third, by focusing on the techniques pertaining to dimensionality reduction, the formulation introduces a new class of applications with the multiple kernel learning framework to address not only the supervised learning problems but also the unsupervised and semi-supervised ones.

Background: MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression at the post-transcriptional level. Recent studies have suggested that miRNAs and transcription factors are primary metazoan gene regulators; however, the crosstalk between them still remains unclear., Methods: We proposed a novel model utilizing functional annotation information to identify significant coregulation between transcriptional and post-transcriptional layers. Based on this model, function-enriched coregulation relationships were discovered and combined into different kinds of functional coregulation networks., Results: We found that miRNAs may engage in a wider diversity of biological processes by coordinating with transcription factors, and this kind of cross-layer coregulation may have higher specificity than intra-layer coregulation. In addition, the coregulation networks reveal several types of network motifs, including feed-forward loops and massive upstream crosstalk. Finally, the expression patterns of these coregulation pairs in normal and tumour tissues were analyzed. Different coregulation types show unique expression correlation trends. More importantly, the disruption of coregulation may be associated with cancers., Conclusion: Our findings elucidate the combinatorial and cooperative properties of transcription factors and miRNAs regulation, and we proposes that the coordinated regulation may play an important role in many biological processes.

Health examinations play a key role in preventive medicine. We propose a health examination system named Health Examination Automatic Logic System (HEALS) to assist clinical workers in improving the total quality of health examinations. Quality of automated inference is confirmed by the zero inference error where during 6 months and 14,773 cases. Automated inference time is less than one second per case in contrast to 2 to 5 min for physicians. The most significant result of efficiency evaluation is that 3,494 of 4,356 (80.2%) cases take less than 3 min per case for producing a report summary. In the evaluation of effectiveness, novice physicians got 18% improvement in making decisions with the assistance of our system. We conclude that a health examination system with a clinical decision system can greatly reduce the mundane burden on clinical workers and markedly improve the quality and efficiency of health examination tasks.

Widmer (J Arthroplasty 2004;19:387) reported a protractor for measuring the anteversion of acetabular cups on radiographs but with limited precision. We intended to improve its precision by trigonometric mathematics. We measured the anteversion of the acetabular cups on 336 simulated radiographs using aforementioned 2 methods. The anteversion measured by Widmer's protractor ranged from 7 degrees to 41 degrees (mean +/- SD = 28.0 degrees +/- 9.8 degrees), and our methods, 5 degrees to 51 degrees (27.7 degrees +/- 13.2 degrees). The mean +/- SD of error by Widmer's protractor was 5.2 +/- 2.5 degrees, and our protractor, 0.8 degrees +/- 0.8 degrees (Student t test, P b .0001). The interobserver study showed the difference between measurements less than 2 degrees for each method. Therefore, the smaller error of our method than that of Widmer implicated a potentially precise measurement of the anteversion (level of evidence: diagnostic study, level II).

Background: Measuring the orientation of acetabular cup after total hip arthroplasty is important for prognosis. The verification of these measurement methods will be easier and more feasible if we can synthesize prosthesis radiographs in each simulated condition. One reported method used an expensive mechanical device with an indeterminable precision. We thus develop a program, THR Simulator, to directly synthesize digital radiographs of prostheses for further analysis.Under Windows platform and using Borland C++ Builder programming tool, we developed the THR Simulator. We first built a mathematical model of acetabulum and femoral head. The data of the real dimension of prosthesis was adopted to generate the radiograph of hip prosthesis. Then with the ray tracing algorithm, we calculated the thickness each X-ray beam passed, and then transformed to grey scale by mapping function which was derived by fitting the exponential function from the phantom image. Finally we could generate a simulated radiograph for further analysis., Results: Using THR Simulator, the users can incorporate many parameters together for radiograph synthesis. These parameters include thickness, film size, tube distance, film distance, anteversion, abduction, upper wear, medial wear, and posterior wear. These parameters are adequate for any radiographic measurement research. This THR Simulator has been used in two studies, and the errors are within 2 degrees for anteversion and 0.2 mm for wearing measurement., Conclusion: We design a program, THR Simulator that can synthesize prosthesis radiographs. Such a program can be applied in future studies for further analysis and validation of measurement of various parameters of pelvis after total hip arthroplasty.

Background: Cobeljić et al. recently reported a numeric table method to provide precise rotational osteotomy which is a well established orthopaedic procedure. The numeric table requires four pages in length that is rather inconvenient during performing an osteotomy operation., Methods: We thus develop our own method by summarizing the data of the four-page table into a small ruler, which is easy to carry and use in operation room. An electrical version of this ruler is also available. We also build a computer model to verify Cobeljić et al. method., Results: The error of Cobeljić et al. is between -37% to 16% (mean +/- SD = -6% +/- 9%). We verify our ruler by calculating the absolute difference between our method and that of Cobeljić et al. The difference is less than 0.1 mm., Conclusion: Our ruler is convenient for practical use for the rotational osteotomy procedure with equal precision. Further clinical verification is needed to justify its real significance.

Orientation of the hip cup is important in total hip arthroplasties. Orientation includes abduction (inclination) and anteversion. Anteversion can be considered as true (anatomic) and planar (radiographic) anteversion. Some measurement methods either are too complicated or are less precise. We developed a new protractor to measure cup orientation using postoperative anteroposterior radiographs centered at the hip. The new protractor measures true and planar anteversion and abduction easily and precisely. We verified its accuracy using a software simulator and simulated 45 radio- graphs of total hip arthroplasties with 15 different anteversions ranging from 15 degrees -29 degrees and 45 actual radiographs of total hip arthroplasties. We then measured the planar ante- version with our method and the method of Lewinnek et al. Maximal errors were 3 degrees and 2.61 degrees , respectively, and mean errors were 0.96 degrees and 1.2 degrees , respectively. The standard deviations were 0.74 degrees with our method and 0.57 degrees with the method of Lewinnek et al. For the real radiographs, the mean of absolute difference between the two methods was 1.34 degrees , and the standard deviation was 1.13 degrees . We found no difference between the two methods and no difference in our findings compared with those of Pradhan.

Detecting critical changes of environments while driving is an important task in driver assistance systems. In this paper, a computational model motivated by human cognitive processing and selective attention is proposed for this purpose. The computational model consists of three major components, referred to as the sensory, perceptual, and conceptual analyzers. The sensory analyzer extracts temporal and spatial information from video sequences. The extracted information serves as the input stimuli to a spatiotemporal attention (STA) neural network embedded in the perceptual analyzer. If consistent stimuli repeatedly innervate the neural network, a focus of attention will be established in the network. The attention pattern associated with the focus, together with the location and direction of motion of the pattern, form what we call a categorical feature. Based on this feature, the class of the attention pattern and, in turn, the change in driving environment corresponding to the class are determined using a configurable adaptive resonance theory (CART) neural network, which is placed in the conceptual analyzer. Various changes in driving environment, both in daytime and at night, have been tested. The experimental results demonstrated the feasibilities of both the proposed computational model and the change detection system.