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http://dx.doi.org/10.2345/0899-8205-57.1.26 | DOI Listing |
Turk Kardiyol Dern Ars
January 2025
Department of Cardiology, Dr Siyami Ersek Thoracic and Cardiovascular Surgery Training Hospital, İstanbul, Türkiye.
Objective: Coronary artery disease (CAD) is the leading cause of morbidity and mortality globally. The growing interest in natural language processing chatbots (NLPCs) has driven their inevitable widespread adoption in healthcare. The purpose of this study was to evaluate the accuracy and reproducibility of responses provided by NLPCs, such as ChatGPT, Gemini, and Bing, to frequently asked questions about CAD.
View Article and Find Full Text PDFNeurosurg Rev
January 2025
Department of Neurosurgery, University Hospital Leipzig, Leipzig, Saxony, Germany.
To assess the predictive accuracy of advanced AI language models and established clinical scales in prognosticating outcomes for patients with aneurysmal subarachnoid hemorrhage (aSAH). This retrospective cohort study included 82 patients suffering from aSAH. We evaluated the predictive efficacy of AtlasGPT and ChatGPT 4.
View Article and Find Full Text PDFBackground: The COVID-19 pandemic has significantly strained healthcare systems globally, leading to an overwhelming influx of patients and exacerbating resource limitations. Concurrently, an "infodemic" of misinformation, particularly prevalent in women's health, has emerged. This challenge has been pivotal for healthcare providers, especially gynecologists and obstetricians, in managing pregnant women's health.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Economics, University of Copenhagen, Copenhagen 1353, Denmark.
We study the adoption of ChatGPT, the icon of Generative AI, using a large-scale survey linked to comprehensive register data in Denmark. Surveying 18,000 workers from 11 exposed occupations, we document that ChatGPT is widespread, especially among younger and less-experienced workers. However, substantial inequalities have emerged.
View Article and Find Full Text PDFJMIR Med Inform
January 2025
Department of Science and Education, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, China.
Background: Large language models (LLMs) have been proposed as valuable tools in medical education and practice. The Chinese National Nursing Licensing Examination (CNNLE) presents unique challenges for LLMs due to its requirement for both deep domain-specific nursing knowledge and the ability to make complex clinical decisions, which differentiates it from more general medical examinations. However, their potential application in the CNNLE remains unexplored.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!