Knee injuries are common in several people, frequently controlling for significant injuries and health care costs. This article explains the role of personalized exercise prescriptions in preventing knee injuries. For this purpose, we used the multic...
Deep convolutional neural networks (CNNs) have seen significant growth in medical image classification applications due to their ability to automate feature extraction, leverage hierarchical learning, and deliver high classification accuracy. However...
Sarcopenia, characterized by progressive loss of muscle mass and function, is a growing public health concern. The ZJU index, a novel metabolic marker, integrates lipid metabolism and glucose regulation parameters. While its association with metaboli...
This study aimed to develop and validate a transformer-based early warning score (TEWS) system for predicting adverse events (AEs) in the emergency department (ED). We conducted a retrospective study analyzing adult ED visits at a tertiary hospital. ...
The estimation of rupture risk in Unruptured Intracranial Aneurysm (UIA) constitutes a major area of clinical interest due to the significant morbidity and mortality rates associated with aneurysm rupture. Classic clinical models based on factors suc...
This study introduces a cognition-enhanced framework for geospatial decision-making by integrating Fuzzy Formal Concept Analysis (FCA), the Surprisingly Popular (SP) method, and a Large Language Model (GPT-4o). Our approach captures cognitive influen...
Various diseases including laminopathies and certain types of cancer are associated with abnormal nuclear mechanical properties that influence cellular and nuclear deformations in complex environments. Recently, microgroove substrates designed to mim...
Dolutegravir and bictegravir are second-generation HIV integrase strand transfer inhibitors (INSTIs) that were previously associated with abnormal weight gain. This monocentric cross-sectional study investigates associations between weight gain durin...
Accurate Lung cancer (LC) identification is a big medical problem in the AI-based healthcare systems. Various deep learning-based methods have been proposed for Lung cancer diagnosis. In this study, we proposed a Deep learning techniques-based integr...
To develop an automated grading model for rectocele (RC) based on radiomics and evaluate its efficacy. This study retrospectively analyzed a total of 9,392 magnetic resonance imaging (MRI) images obtained from 222 patients who underwent dynamic magne...
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