BACKGROUND: The safety planning intervention (SPI) is a suicide prevention intervention that results in a written plan to help patients reduce suicide risk. High-quality safety plans-that is, those that are the most complete, personalized, and specif...
BACKGROUND: The rapid growth of social media as an information channel has enabled the swift spread of inaccurate or false health information, significantly impacting public health. This widespread dissemination of misinformation has caused confusion...
BACKGROUND: High-quality clinical chains-of-thought (CoTs) are essential for explainable medical artificial intelligence (AI); yet, their development is limited by data scarcity. Large language models can generate medical CoTs, but their clinical rel...
Large language models (LLMs) offer significant potential for constructing commonsense knowledge graphs from text, demonstrating adaptability across diverse domains. However, their effectiveness varies significantly with domain-specific language, high...
BACKGROUND: Large language models (LLMs) have emerged as promising tools for enhancing public access to medical information, particularly for chronic diseases such as atherosclerotic cardiovascular disease (ASCVD). However, their effectiveness in pat...
Neuropsychological assessments are essential for evaluating functional status and guiding surgical planning in patients with brain tumors. However, their complexity may hinder interpretation for patients and junior clinicians. Large language model (L...
BACKGROUND: Data collected in controlled settings typically results in high-quality datasets. However, in real-world applications, the quality of data collection is often compromised. It is well established that the quality of a dataset significantly...
Humans can now emulate language in silica-based neural networks, but we remain ignorant about how language emerged in carbon-based neural networks in the first place. This gap represents not merely a scientific blind spot, but a unique opportunity to...
Journal of cancer research and clinical oncology
Dec 20, 2025
PURPOSE: With increasing reliance on large language models (LLMs) for health information, this study evaluated reliability and quality, understandability, actionability, readability and misinformation risk of responses from LLMs to oral health concer...
In this study, we have applied advanced masked language models (MLMs)-BERT, DistilBERT, ELECTRA, and RoBERTa-to infer missing and misinterpreted values in comprehensive family register data. Our data compiles Daegu-bu household register books, trienn...
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