This study developed a machine learning model to predict stillbirth using retrospective data from 32,953 singleton pregnancies at multi-centers in South Korea. Variables were collected at baseline, E1 (before 13 weeks of pregnancy), and T0 (before 28...
Atrial fibrillation (AF) and aortic stenosis (AS) are two common progressive conditions affecting older persons that share pathobiological pathways. Early detection of AS is critical for improving outcomes, but no prediction tool exists to inform dec...
Globalization is claimed to have a homogenizing effect, reducing pronounced local cultural differences. Indoor living spaces are among the most vivid expressions of local culture, yet they remain underexplored in this context. Our visual AI framework...
Hypoproteinemia is a common complication across patients receiving maintenance hemodialysis (MHD). Moreover, it is associated with increased risks of cardiovascular events, infection risk, and mortality. This study aimed to construct a classification...
The tumor microenvironment (TME) is associated with tumor prognosis, immunotherapy response, and prognosis in patients. Here, we hypothesized that the entire TME in pathology image is associated with the survival time prediction. To address this hypo...
Deep learning models show promise in accelerating the design and optimization of antimicrobial peptides (AMPs), but current methods face challenges, such as low success rates, or large virtual library scales. In this study, we introduce DLFea4AMPGen,...
Osteoarthritis (OA) is a widespread joint disorder that has emerged as a significant global healthcare challenge. Over the past decade, advancements in material science and medicine have transformed the development of functional materials aimed at ad...
OBJECTIVES: To describe the implementation of a multidisciplinary, ethically grounded hackathon as a model to develop and evaluate generative AI (GenAI) solutions for real-world clinical challenges within a hospital setting.
OBJECTIVES: Antimicrobial resistance is a critical public health threat. Large language models (LLMs) show great capability for providing health information. This study evaluates the effectiveness of LLMs in providing information on antibiotic use an...
OBJECTIVES: To evaluate the impact of implementing a multidisciplinary integrated telehealth platform in central Taiwan on healthcare accessibility, emergency response and chronic disease management.
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