William Rojas-Carabali, Alok Sen, Aniruddha Agarwal, Gavin Tan, Carol Y Cheung, Andres Rousselot, Rajdeep Agrawal, Renee Liu, Carlos Cifuentes-González, Tobias Elze, John H Kempen, Lucia Sobrin, Quan Dong Nguyen, Alejandra de-la-Torre, Bernett Lee, Vishali Gupta, Rupesh Agrawal
{"title":"聊天机器人与人类专家：评估聊天机器人在葡萄膜炎中的诊断性能以及人工智能在眼科应用的前景。","authors":"William Rojas-Carabali, Alok Sen, Aniruddha Agarwal, Gavin Tan, Carol Y Cheung, Andres Rousselot, Rajdeep Agrawal, Renee Liu, Carlos Cifuentes-González, Tobias Elze, John H Kempen, Lucia Sobrin, Quan Dong Nguyen, Alejandra de-la-Torre, Bernett Lee, Vishali Gupta, Rupesh Agrawal","doi":"10.1080/09273948.2023.2266730","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>To assess the diagnostic performance of two chatbots, ChatGPT and Glass, in uveitis diagnosis compared to renowned uveitis specialists, and evaluate clinicians' perception about utilizing artificial intelligence (AI) in ophthalmology practice.</p><p><strong>Methods: </strong>Six cases were presented to uveitis experts, ChatGPT (version 3.5 and 4.0) and Glass 1.0, and diagnostic accuracy was analyzed. Additionally, a survey about the emotions, confidence in utilizing AI-based tools, and the likelihood of incorporating such tools in clinical practice was done.</p><p><strong>Results: </strong>Uveitis experts accurately diagnosed all cases (100%), while ChatGPT achieved a diagnostic success rate of 66% and Glass 1.0 achieved 33%. Most attendees felt excited or optimistic about utilizing AI in ophthalmology practice. Older age and high level of education were positively correlated with increased inclination to adopt AI-based tools.</p><p><strong>Conclusions: </strong>ChatGPT demonstrated promising diagnostic capabilities in uveitis cases and ophthalmologist showed enthusiasm for the integration of AI into clinical practice.</p>","PeriodicalId":19406,"journal":{"name":"Ocular Immunology and Inflammation","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Chatbots Vs. Human Experts: Evaluating Diagnostic Performance of Chatbots in Uveitis and the Perspectives on AI Adoption in Ophthalmology.\",\"authors\":\"William Rojas-Carabali, Alok Sen, Aniruddha Agarwal, Gavin Tan, Carol Y Cheung, Andres Rousselot, Rajdeep Agrawal, Renee Liu, Carlos Cifuentes-González, Tobias Elze, John H Kempen, Lucia Sobrin, Quan Dong Nguyen, Alejandra de-la-Torre, Bernett Lee, Vishali Gupta, Rupesh Agrawal\",\"doi\":\"10.1080/09273948.2023.2266730\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>To assess the diagnostic performance of two chatbots, ChatGPT and Glass, in uveitis diagnosis compared to renowned uveitis specialists, and evaluate clinicians' perception about utilizing artificial intelligence (AI) in ophthalmology practice.</p><p><strong>Methods: </strong>Six cases were presented to uveitis experts, ChatGPT (version 3.5 and 4.0) and Glass 1.0, and diagnostic accuracy was analyzed. Additionally, a survey about the emotions, confidence in utilizing AI-based tools, and the likelihood of incorporating such tools in clinical practice was done.</p><p><strong>Results: </strong>Uveitis experts accurately diagnosed all cases (100%), while ChatGPT achieved a diagnostic success rate of 66% and Glass 1.0 achieved 33%. Most attendees felt excited or optimistic about utilizing AI in ophthalmology practice. Older age and high level of education were positively correlated with increased inclination to adopt AI-based tools.</p><p><strong>Conclusions: </strong>ChatGPT demonstrated promising diagnostic capabilities in uveitis cases and ophthalmologist showed enthusiasm for the integration of AI into clinical practice.</p>\",\"PeriodicalId\":19406,\"journal\":{\"name\":\"Ocular Immunology and Inflammation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ocular Immunology and Inflammation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/09273948.2023.2266730\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/10/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"OPHTHALMOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ocular Immunology and Inflammation","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/09273948.2023.2266730","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/10/13 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}
Chatbots Vs. Human Experts: Evaluating Diagnostic Performance of Chatbots in Uveitis and the Perspectives on AI Adoption in Ophthalmology.
Purpose: To assess the diagnostic performance of two chatbots, ChatGPT and Glass, in uveitis diagnosis compared to renowned uveitis specialists, and evaluate clinicians' perception about utilizing artificial intelligence (AI) in ophthalmology practice.
Methods: Six cases were presented to uveitis experts, ChatGPT (version 3.5 and 4.0) and Glass 1.0, and diagnostic accuracy was analyzed. Additionally, a survey about the emotions, confidence in utilizing AI-based tools, and the likelihood of incorporating such tools in clinical practice was done.
Results: Uveitis experts accurately diagnosed all cases (100%), while ChatGPT achieved a diagnostic success rate of 66% and Glass 1.0 achieved 33%. Most attendees felt excited or optimistic about utilizing AI in ophthalmology practice. Older age and high level of education were positively correlated with increased inclination to adopt AI-based tools.
Conclusions: ChatGPT demonstrated promising diagnostic capabilities in uveitis cases and ophthalmologist showed enthusiasm for the integration of AI into clinical practice.
期刊介绍：
Ocular Immunology & Inflammation ranks 18 out of 59 in the Ophthalmology Category.Ocular Immunology and Inflammation is a peer-reviewed, scientific publication that welcomes the submission of original, previously unpublished manuscripts directed to ophthalmologists and vision scientists. Published bimonthly, the journal provides an international medium for basic and clinical research reports on the ocular inflammatory response and its control by the immune system. The journal publishes original research papers, case reports, reviews, letters to the editor, meeting abstracts, and invited editorials.
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