BACKGROUND: Surgical consent forms convey critical information; yet, their complex language can limit patient comprehension. Large language models (LLMs) can simplify complex information and improve readability, but evidence of the impact of LLM-gene...
Atopic dermatitis (AD) is an inflammatory skin disease with immunological and environmental triggers that reduces the quality of life and increases the burden on health services. It is thus important to establish effective surveillance and diagnosis ...
BACKGROUND: Cardiovascular and cerebrovascular diseases significantly contribute to global mortality and disability. The shift to outpatient postoperative care, accelerated by the COVID-19 pandemic, emphasizes the need for effective management of pos...
Our study aims to improve the prediction performance of machine learning (ML) models by addressing false records (i.e., false positive, false negative, or missingness) in binary categorical variables in electronic medical records (EMRs) using propens...
INTRODUCTION: Epidemic modeling is crucial for understanding and predicting infectious disease spread. To capture the complexity of real-world transmission, dynamic interactions between individuals with spatial heterogeneity must be considered. This ...
Recent achievements in the fields of deep learning and remote sensing have led to their application in monitoring river water quality. One of the most researched methods is the estimation of total suspended solid (TSS) concentrations using multispect...
Traditional clinical risk assessment tools proved inadequate for reliably identifying individuals at high risk for suicidal behavior. As a result, machine learning (ML) techniques have become progressively incorporated into psychiatric care. This stu...
The increases in the older population, the prevalence of dementia, and the resulting social costs are burdensome to individuals, families, and the nation. This study examines whether the social robot PIO program intervention is effective for cognitiv...
International journal of medical informatics
Apr 21, 2025
BACKGROUND: Explainable Artificial Intelligence (XAI) is increasingly vital in healthcare, where clinicians need to understand and trust AI-generated recommendations. However, the impact of AI model explanations on clinical decision-making remains in...
Metabolic syndrome (MetS) is a major global public health concern due to its rising prevalence and association with increased risks of cardiovascular disease and type 2 diabetes. Emerging evidence suggests that environmental chemical exposures may pl...
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