Traditional methods for language assessment in psychiatric and neurological disorders, such as clinical scales, are time and resource intensive, and can be hampered by rater biases and subjectivity. These limitations can compromise their reliability ...
BACKGROUND: Addressing the complex medical and psychosocial needs of older adults is increasingly difficult in resource-limited care settings. In this context, socially assistive robots (SARs) provide support and practical functions such as orientati...
BACKGROUND: Large language models (LLMs) are increasingly used in medical education for feedback and grading; yet their role in postgraduate examination preparation remains uncertain due to inconsistent grading, hallucinations, and user acceptance.
Large language models (LLMs) are increasingly used in healthcare and medical education, but their performance on institution-authored multiple-choice questions (MCQs), particularly with negative marking, remains unclear. To compare the examination pe...
This study compared the performance of classical feature-based machine learning models (CMLs) and large language models (LLMs) in predicting COVID-19 mortality using high-dimensional tabular data from 9,134 patients across four hospitals. Seven CML m...
Proceedings of the National Academy of Sciences of the United States of America
Nov 26, 2025
Subjective well-being is central to economic, medical, and policy decision-making. We evaluate whether large language models (LLMs) can provide valid predictions of well-being across global populations. Using natural-language profiles from 64,000 ind...
BACKGROUND: To evaluate the credibility of large language models (LLMs) compared to American Association of Orthodontists (AAO) and British Orthodontic Society (BOS) guides regarding nutritional guidelines for orthodontic patients.
While deep learning has enabled the decoding of language from intracranial brain recordings, achieving this with non-invasive recordings remains an open challenge. We introduce a deep learning pipeline to decode individual words from electro- (EEG) a...
Large Language Models (LLMs) offer a framework for understanding language processing in the human brain. Unlike traditional models, LLMs represent words and context through layered numerical embeddings. Here, we demonstrate that LLMs' layer hierarchy...
Online social networks are currently the most widely utilized interactive media for interpersonal communication, emotional expression, and information sharing. Despite the helpful and fascinating content, unfortunately, inappropriate or abusive conte...
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