 Evaluation of the efficacy of ChatGPT versus medical students in clinical case resolutionAlberto Bustillos, Fernanda Marizande, Andrea Cevallos, Diana Bustillos, Cristina Arteaga and Fabricio Vásquez de la Bandera Data and Metadata, 2024, vol. 3, .433 Abstract: Introduction: The use of artificial intelligence (AI) in medical education has gained relevance, and tools like ChatGPT offer support in solving clinical cases. This study compared the average performance of ChatGPT against medical students to evaluate its potential as an educational tool. Methods: A cross-sectional quantitative study was conducted with 110 sixth-semester medical students from the Technical University of Ambato. Four clinical cases were designed, covering cardiology, endocrinology, gastroenterology, and neurology scenarios. Multiple-choice questions were used to assess both the participants and ChatGPT. Data were analyzed using the Student's t-test for independent samples. Results: ChatGPT outperformed the students in all cases, with an average score of 8.25 compared to 7.35 for the students. A statistically significant difference was found between the two groups (p = 0.0293). Conclusions: ChatGPT demonstrated superior performance in solving clinical cases compared to medical students. However, limitations such as potential inaccuracies in information highlight the need for further studies and supervision when integrating AI into medical education. Date: 2024 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:dbk:datame:v:3:y:2024:i::p:.433:id:1056294dm2024433 DOI: 10.56294/dm2024.433 Access Statistics for this article More articles in Data and Metadata from AG Editor |
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