دورية أكاديمية
A vignette-based evaluation of ChatGPT's ability to provide appropriate and equitable medical advice across care contexts.
| العنوان: | A vignette-based evaluation of ChatGPT's ability to provide appropriate and equitable medical advice across care contexts. |
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| المؤلفون: | Nastasi AJ; Department of Emergency Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA. Anthony.Nastasi@pennmedicine.upenn.edu., Courtright KR; Perelman School of Medicine, Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA, USA.; Division of Pulmonary, Allergy, & Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Perelman School of Medicine, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.; Perelman School of Medicine, Penn Palliative Care Program, University of Pennsylvania, Philadelphia, PA, USA., Halpern SD; Perelman School of Medicine, Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA, USA.; Division of Pulmonary, Allergy, & Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Perelman School of Medicine, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA., Weissman GE; Perelman School of Medicine, Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA, USA.; Division of Pulmonary, Allergy, & Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Perelman School of Medicine, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.; Perelman School of Medicine, Penn Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA. |
| المصدر: | Scientific reports [Sci Rep] 2023 Oct 19; Vol. 13 (1), pp. 17885. Date of Electronic Publication: 2023 Oct 19. |
| نوع المنشور: | Journal Article; Research Support, N.I.H., Extramural |
| اللغة: | English |
| بيانات الدورية: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: London : Nature Publishing Group, copyright 2011- |
| مواضيع طبية MeSH: | Insurance Coverage* , Language*, Humans ; Female ; Social Factors ; Uterus |
| مستخلص: | ChatGPT is a large language model trained on text corpora and reinforced with human supervision. Because ChatGPT can provide human-like responses to complex questions, it could become an easily accessible source of medical advice for patients. However, its ability to answer medical questions appropriately and equitably remains unknown. We presented ChatGPT with 96 advice-seeking vignettes that varied across clinical contexts, medical histories, and social characteristics. We analyzed responses for clinical appropriateness by concordance with guidelines, recommendation type, and consideration of social factors. Ninety-three (97%) responses were appropriate and did not explicitly violate clinical guidelines. Recommendations in response to advice-seeking questions were completely absent (N = 34, 35%), general (N = 18, 18%), or specific (N = 44, 46%). 53 (55%) explicitly considered social factors like race or insurance status, which in some cases changed clinical recommendations. ChatGPT consistently provided background information in response to medical questions but did not reliably offer appropriate and personalized medical advice. (© 2023. Springer Nature Limited.) |
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| معلومات مُعتمدة: | K23 HL141639 United States HL NHLBI NIH HHS; R01AG073384 United States NH NIH HHS |
| تواريخ الأحداث: | Date Created: 20231019 Date Completed: 20231023 Latest Revision: 20240210 |
| رمز التحديث: | 20240210 |
| مُعرف محوري في PubMed: | PMC10587094 |
| DOI: | 10.1038/s41598-023-45223-y |
| PMID: | 37857839 |
| قاعدة البيانات: | MEDLINE |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 2045-2322 |
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| DOI: | 10.1038/s41598-023-45223-y |