BACKGROUND: The high rate of repeat attempts among individuals who have previously attempted suicide presents a critical challenge in public health and suicide prevention. While early and targeted intervention is crucial for this high-risk group, eff...
BACKGROUND: Identifying key areas of brain dysfunction in mental illness is critical for developing precision diagnosis and treatment. This study aimed to develop region-specific brain aging trajectory prediction models using multimodal magnetic reso...
BACKGROUND: Advancements in artificial intelligence (AI) have driven substantial breakthroughs in computer-aided detection (CAD) for chest x-ray (CXR) imaging. The National Taiwan University Hospital research team previously developed an AI-based eme...
BACKGROUND: Hepatic encephalopathy (HE) contributes significantly to mortality among patients with liver cirrhosis. Early prediction of HE is essential for clinical decision-making, yet remains challenging-particularly in noncancer-related cirrhosis ...
Previous air pollution modeling studies have predominantly emphasized horizontal distributions, overlooking the critical vertical variability of pollutant concentrations in urban environments. Therefore, the three-dimensional (3-D) behavior of air po...
Lung cancer remains the leading cause of cancer deaths in many developed countries, primarily due to late-stage diagnosis. Histopathology, the gold standard for diagnosis, often results in semi-structured pathological reports containing complex infor...
OBJECTIVES: Unplanned pneumonia readmissions increase patient morbidity, mortality and healthcare costs. Among pneumonia patients, the middle-aged and elderly (≥45 years old) have a significantly higher risk of readmission compared with the young. Gi...
BACKGROUND: Early diagnosis of low ejection fraction (EF) remains challenging despite being a treatable condition. This study aimed to evaluate the effectiveness of an electrocardiogram (ECG)-based artificial intelligence (AI)-assisted clinical decis...
Type 2 diabetes (T2D) is influenced by lifestyle, genetics, and environmental conditions. By utilizing machine learning techniques, we can enhance the precision of T2D risk prediction by analyzing the complex interactions among these variables. This...
International journal of medical informatics
Apr 26, 2025
BACKGROUND: The aging population is driving increased healthcare demands and costs, prompting the need for effective home healthcare programs. Accurate patient assessment is essential for optimizing resource allocation and tailoring services.
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