The widespread use of 3D stereoscopic technology has drawn attention to the problem of visual discomfort, several studies have used EEG to assess visual comfort and discomfort phenomena, but there is a lack of scientific basis for the selection of el...
Suicide prevention is currently a global public health priority, since suicide has been a prevalent cause of death or potential loss of life. Multiple factors contribute to suicide risk, such as depression and a history of attempted suicide among oth...
BACKGROUND: High-resolution computed tomography (HRCT) is helpful for diagnosing interstitial lung diseases (ILD), but it largely depends on the experience of physicians. Herein, our study aims to develop a deep-learning-based classification model to...
This study aims to develop a robust and accurate model to forecast 30-day readmissions for patients with diabetes by leveraging machine learning techniques. Diabetes, being a chronic condition with complex care needs, often leads to frequent hospital...
Gastric cancer (GC) ranks as the fifth most commonly diagnosed malignancy and the fourth leading cause of cancer-related mortality worldwide. The integration of machine learning in the analysis of GC metabolomics data for biomarker identification rem...
Applying machine learning algorithms to physical signals is always challenging since undesirable events can occur when signals are acquired outside a controlled environment. Among several applications, movement recognition through sEMG signals is esp...
INTRODUCTION: Increased LDL cholesterol is one of the main risk factors for cardiovascular diseases; therefore, adequate therapy reduces the risk of developing cardiovascular disease. Artificial intelligence (AI) is a tool that can significantly help...
BACKGROUND: Pediatric emergency departments face overcrowding, often driven by non-urgent consultations. Telephone triage, supported by clinical decision support systems (CDSSs), offers a potential solution to improve decision accuracy and reduce unn...
BACKGROUND: Breast arterial calcification (BAC) is increasingly recognized as a significant indicator of cardiovascular risk, necessitating improvements in detection and quantification methods through mammographic screening.
OBJECTIVE: Generating discharge summaries is a crucial yet time-consuming task in clinical practice, essential for conveying pertinent patient information and facilitating continuity of care. Recent advancements in large language models (LLMs) have s...
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