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Evaluating large language models on medical, lay-language, and self-reported descriptions of genetic conditions.
Am J Hum Genet
September 2024
Medical Genomics Unit, National Human Genome Research Institute, National Institutes of Health, 10 Center Dr, Bethesda, MD 20892, USA. Electronic address:
Large language models (LLMs) are generating interest in medical settings. For example, LLMs can respond coherently to medical queries by providing plausible differential diagnoses based on clinical notes. However, there are many questions to explore, such as evaluating differences between open- and closed-source LLMs as well as LLM performance on queries from both medical and non-medical users.
View Article and Find Full Text PDFThe Key Ripper: a specialized fixed suture-cutting device to facilitate drain removal.
Surg Today
July 2024
International Centre for Lymphedema, Hiroshima University Hospital, Hiroshima, Japan.
Article Synopsis
- - A new device has been created to safely cut sutures that hold post-surgical drains in place.
- - This specialized tool simplifies the removal process, making it easier compared to traditional methods like scissors or scalpels.
- - The innovation aims to enhance safety during the drain removal procedure for patients.
Diabetes misconceptions, seriousness, motivation, self-efficacy and stigma: A cross-sectional comparison of eight Australian diabetes communication campaign videos.
Diabet Med
November 2024
School of Psychology, Deakin University, Geelong, Victoria, Australia.
Aim: This study examines potential intended (attitudes, motivation and self-efficacy) and unintended (stigmatisation of diabetes) consequences of past Australian National Diabetes Week campaign videos. Further, outcomes are compared by the extent to which participants perceived their allocated video as stigmatising diabetes.
Methods: In this cross-sectional, ten-arm study, participants (adults with or without diabetes; 1:2 ratio) were randomly allocated to view one of eight archival diabetes campaign videos (intervention), or either an active or passive control group.
Approximating facial expression effects on diagnostic accuracy via generative AI in medical genetics.
Bioinformatics
June 2024
Medical Genomics Unit, Medical Genetics Branch, National Human Genome Research Institute, Bethesda, MA 20892, United States.
Artificial intelligence (AI) is increasingly used in genomics research and practice, and generative AI has garnered significant recent attention. In clinical applications of generative AI, aspects of the underlying datasets can impact results, and confounders should be studied and mitigated. One example involves the facial expressions of people with genetic conditions.
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