TY - JOUR
T1 - Chatbots Vs. Human Experts
T2 - Evaluating Diagnostic Performance of Chatbots in Uveitis and the Perspectives on AI Adoption in Ophthalmology
AU - Rojas-Carabali, William
AU - Sen, Alok
AU - Agarwal, Aniruddha
AU - Tan, Gavin
AU - Cheung, Carol Y.
AU - Rousselot, Andres
AU - Agrawal, Rajdeep
AU - Liu, Renee
AU - Cifuentes-González, Carlos
AU - Elze, Tobias
AU - Kempen, John H.
AU - Sobrin, Lucia
AU - Nguyen, Quan Dong
AU - de-la-Torre, Alejandra
AU - Lee, Bernett
AU - Gupta, Vishali
AU - Agrawal, Rupesh
N1 - Publisher Copyright:
© 2023 Taylor & Francis Group, LLC.
PY - 2023/10/13
Y1 - 2023/10/13
N2 - 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.
AB - 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.
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U2 - 10.1080/09273948.2023.2266730
DO - 10.1080/09273948.2023.2266730
M3 - Article
C2 - 37831553
AN - SCOPUS:85174047282
SN - 0927-3948
JO - Ocular Immunology and Inflammation
JF - Ocular Immunology and Inflammation
ER -
