Ryan DeCook BS , Brian T. Muffly MD , Sania Mahmood MD , Christopher T. Holland MD, MS , Ayomide M. Ayeni BS , Michael P. Ast MD , Michael P. Bolognese MD , George N. Guild III MD , Neil P. Sheth MD , Christian A. Pean MD, MS , Ajay Premkumar MD, MPH
{"title":"人工智能生成的全关节关节置换术毕业医学教育内容：将 ChatGPT 与骨科研究员进行比较","authors":"Ryan DeCook BS , Brian T. Muffly MD , Sania Mahmood MD , Christopher T. Holland MD, MS , Ayomide M. Ayeni BS , Michael P. Ast MD , Michael P. Bolognese MD , George N. Guild III MD , Neil P. Sheth MD , Christian A. Pean MD, MS , Ajay Premkumar MD, MPH","doi":"10.1016/j.artd.2024.101412","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Artificial intelligence (AI) in medicine has primarily focused on diagnosing and treating diseases and assisting in the development of academic scholarly work. This study aimed to evaluate a new use of AI in orthopaedics: content generation for professional medical education. Quality, accuracy, and time were compared between content created by ChatGPT and orthopaedic surgery clinical fellows.</p></div><div><h3>Methods</h3><p>ChatGPT and 3 orthopaedic adult reconstruction fellows were tasked with creating educational summaries of 5 total joint arthroplasty-related topics. Responses were evaluated across 5 domains by 4 blinded reviewers from different institutions who are all current or former total joint arthroplasty fellowship directors or national arthroplasty board review course directors.</p></div><div><h3>Results</h3><p>ChatGPT created better orthopaedic content than fellows when mean aggregate scores for all 5 topics and domains were compared (P ≤ .001). The only domain in which fellows outperformed ChatGPT was the integration of key points and references (<em>P</em> = .006). ChatGPT outperformed the fellows in response time, averaging 16.6 seconds vs the fellows' 94 minutes per prompt (<em>P</em> = .002).</p></div><div><h3>Conclusions</h3><p>With its efficient and accurate content generation, the current findings underscore ChatGPT's potential as an adjunctive tool to enhance orthopaedic arthroplasty graduate medical education. Future studies are warranted to explore AI's role further and optimize its utility in augmenting the educational development of arthroplasty trainees.</p></div>","PeriodicalId":37940,"journal":{"name":"Arthroplasty Today","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352344124000979/pdfft?md5=b39156562d6faa20b8dee18cc86da2e5&pid=1-s2.0-S2352344124000979-main.pdf","citationCount":"0","resultStr":"{\"title\":\"AI-Generated Graduate Medical Education Content for Total Joint Arthroplasty: Comparing ChatGPT Against Orthopaedic Fellows\",\"authors\":\"Ryan DeCook BS , Brian T. Muffly MD , Sania Mahmood MD , Christopher T. Holland MD, MS , Ayomide M. Ayeni BS , Michael P. Ast MD , Michael P. Bolognese MD , George N. Guild III MD , Neil P. Sheth MD , Christian A. Pean MD, MS , Ajay Premkumar MD, MPH\",\"doi\":\"10.1016/j.artd.2024.101412\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Artificial intelligence (AI) in medicine has primarily focused on diagnosing and treating diseases and assisting in the development of academic scholarly work. This study aimed to evaluate a new use of AI in orthopaedics: content generation for professional medical education. Quality, accuracy, and time were compared between content created by ChatGPT and orthopaedic surgery clinical fellows.</p></div><div><h3>Methods</h3><p>ChatGPT and 3 orthopaedic adult reconstruction fellows were tasked with creating educational summaries of 5 total joint arthroplasty-related topics. Responses were evaluated across 5 domains by 4 blinded reviewers from different institutions who are all current or former total joint arthroplasty fellowship directors or national arthroplasty board review course directors.</p></div><div><h3>Results</h3><p>ChatGPT created better orthopaedic content than fellows when mean aggregate scores for all 5 topics and domains were compared (P ≤ .001). The only domain in which fellows outperformed ChatGPT was the integration of key points and references (<em>P</em> = .006). ChatGPT outperformed the fellows in response time, averaging 16.6 seconds vs the fellows' 94 minutes per prompt (<em>P</em> = .002).</p></div><div><h3>Conclusions</h3><p>With its efficient and accurate content generation, the current findings underscore ChatGPT's potential as an adjunctive tool to enhance orthopaedic arthroplasty graduate medical education. Future studies are warranted to explore AI's role further and optimize its utility in augmenting the educational development of arthroplasty trainees.</p></div>\",\"PeriodicalId\":37940,\"journal\":{\"name\":\"Arthroplasty Today\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2352344124000979/pdfft?md5=b39156562d6faa20b8dee18cc86da2e5&pid=1-s2.0-S2352344124000979-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Arthroplasty Today\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352344124000979\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ORTHOPEDICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Arthroplasty Today","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352344124000979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
AI-Generated Graduate Medical Education Content for Total Joint Arthroplasty: Comparing ChatGPT Against Orthopaedic Fellows
Background
Artificial intelligence (AI) in medicine has primarily focused on diagnosing and treating diseases and assisting in the development of academic scholarly work. This study aimed to evaluate a new use of AI in orthopaedics: content generation for professional medical education. Quality, accuracy, and time were compared between content created by ChatGPT and orthopaedic surgery clinical fellows.
Methods
ChatGPT and 3 orthopaedic adult reconstruction fellows were tasked with creating educational summaries of 5 total joint arthroplasty-related topics. Responses were evaluated across 5 domains by 4 blinded reviewers from different institutions who are all current or former total joint arthroplasty fellowship directors or national arthroplasty board review course directors.
Results
ChatGPT created better orthopaedic content than fellows when mean aggregate scores for all 5 topics and domains were compared (P ≤ .001). The only domain in which fellows outperformed ChatGPT was the integration of key points and references (P = .006). ChatGPT outperformed the fellows in response time, averaging 16.6 seconds vs the fellows' 94 minutes per prompt (P = .002).
Conclusions
With its efficient and accurate content generation, the current findings underscore ChatGPT's potential as an adjunctive tool to enhance orthopaedic arthroplasty graduate medical education. Future studies are warranted to explore AI's role further and optimize its utility in augmenting the educational development of arthroplasty trainees.
期刊介绍：
Arthroplasty Today is a companion journal to the Journal of Arthroplasty. The journal Arthroplasty Today brings together the clinical and scientific foundations for joint replacement of the hip and knee in an open-access, online format. Arthroplasty Today solicits manuscripts of the highest quality from all areas of scientific endeavor that relate to joint replacement or the treatment of its complications, including those dealing with patient outcomes, economic and policy issues, prosthetic design, biomechanics, biomaterials, and biologic response to arthroplasty. The journal focuses on case reports. It is the purpose of Arthroplasty Today to present material to practicing orthopaedic surgeons that will keep them abreast of developments in the field, prove useful in the care of patients, and aid in understanding the scientific foundation of this subspecialty area of joint replacement. The international members of the Editorial Board provide a worldwide perspective for the journal''s area of interest. Their participation ensures that each issue of Arthroplasty Today provides the reader with timely, peer-reviewed articles of the highest quality.
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