Can ChatGPT-4 Diagnose and Treat Like an Orthopaedic Surgeon? Testing Clinical Decision Making and Diagnostic Ability in Soft-Tissue Pathologies of the Foot and Ankle.
Hayden Hartman, Maritza Diane Essis, Wei Shao Tung, Irvin Oh, Sean Peden, Arianna L Gianakos
{"title":"Can ChatGPT-4 Diagnose and Treat Like an Orthopaedic Surgeon? Testing Clinical Decision Making and Diagnostic Ability in Soft-Tissue Pathologies of the Foot and Ankle.","authors":"Hayden Hartman, Maritza Diane Essis, Wei Shao Tung, Irvin Oh, Sean Peden, Arianna L Gianakos","doi":"10.5435/JAAOS-D-24-00595","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>ChatGPT-4, a chatbot with an ability to carry human-like conversation, has attracted attention after demonstrating aptitude to pass professional licensure examinations. The purpose of this study was to explore the diagnostic and decision-making capacities of ChatGPT-4 in clinical management specifically assessing for accuracy in the identification and treatment of soft-tissue foot and ankle pathologies.</p><p><strong>Methods: </strong>This study presented eight soft-tissue-related foot and ankle cases to ChatGPT-4, with each case assessed by three fellowship-trained foot and ankle orthopaedic surgeons. The evaluation system included five criteria within a Likert scale, scoring from 5 (lowest) to 25 (highest possible).</p><p><strong>Results: </strong>The average sum score of all cases was 22.0. The Morton neuroma case received the highest score (24.7), and the peroneal tendon tear case received the lowest score (16.3). Subgroup analyses of each of the 5 criterion using showed no notable differences in surgeon grading. Criteria 3 (provide alternative treatments) and 4 (provide comprehensive information) were graded markedly lower than criteria 1 (diagnose), 2 (treat), and 5 (provide accurate information) (for both criteria 3 and 4: P = 0.007; P = 0.032; P < 0.0001). Criteria 5 was graded markedly higher than criteria 2, 3, and 4 (P = 0.02; P < 0.0001; P < 0.0001).</p><p><strong>Conclusion: </strong>This study demonstrates that ChatGPT-4 effectively diagnosed and provided reliable treatment options for most soft-tissue foot and ankle cases presented, noting consistency among surgeon evaluators. Individual criterion assessment revealed that ChatGPT-4 was most effective in diagnosing and suggesting appropriate treatment, but limitations were seen in the chatbot's ability to provide comprehensive information and alternative treatment options. In addition, the chatbot successfully did not suggest fabricated treatment options, a common concern in prior literature. This resource could be useful for clinicians seeking reliable patient education materials without the fear of inconsistencies, although comprehensive information beyond treatment may be limited.</p>","PeriodicalId":51098,"journal":{"name":"Journal of the American Academy of Orthopaedic Surgeons","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Academy of Orthopaedic Surgeons","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.5435/JAAOS-D-24-00595","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: ChatGPT-4, a chatbot with an ability to carry human-like conversation, has attracted attention after demonstrating aptitude to pass professional licensure examinations. The purpose of this study was to explore the diagnostic and decision-making capacities of ChatGPT-4 in clinical management specifically assessing for accuracy in the identification and treatment of soft-tissue foot and ankle pathologies.
Methods: This study presented eight soft-tissue-related foot and ankle cases to ChatGPT-4, with each case assessed by three fellowship-trained foot and ankle orthopaedic surgeons. The evaluation system included five criteria within a Likert scale, scoring from 5 (lowest) to 25 (highest possible).
Results: The average sum score of all cases was 22.0. The Morton neuroma case received the highest score (24.7), and the peroneal tendon tear case received the lowest score (16.3). Subgroup analyses of each of the 5 criterion using showed no notable differences in surgeon grading. Criteria 3 (provide alternative treatments) and 4 (provide comprehensive information) were graded markedly lower than criteria 1 (diagnose), 2 (treat), and 5 (provide accurate information) (for both criteria 3 and 4: P = 0.007; P = 0.032; P < 0.0001). Criteria 5 was graded markedly higher than criteria 2, 3, and 4 (P = 0.02; P < 0.0001; P < 0.0001).
Conclusion: This study demonstrates that ChatGPT-4 effectively diagnosed and provided reliable treatment options for most soft-tissue foot and ankle cases presented, noting consistency among surgeon evaluators. Individual criterion assessment revealed that ChatGPT-4 was most effective in diagnosing and suggesting appropriate treatment, but limitations were seen in the chatbot's ability to provide comprehensive information and alternative treatment options. In addition, the chatbot successfully did not suggest fabricated treatment options, a common concern in prior literature. This resource could be useful for clinicians seeking reliable patient education materials without the fear of inconsistencies, although comprehensive information beyond treatment may be limited.
期刊介绍：
The Journal of the American Academy of Orthopaedic Surgeons was established in the fall of 1993 by the Academy in response to its membership’s demand for a clinical review journal. Two issues were published the first year, followed by six issues yearly from 1994 through 2004. In September 2005, JAAOS began publishing monthly issues.
Each issue includes richly illustrated peer-reviewed articles focused on clinical diagnosis and management. Special features in each issue provide commentary on developments in pharmacotherapeutics, materials and techniques, and computer applications.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
