医学
医学诊断
葡萄膜炎
聊天机器人
诊断准确性
验光服务
眼科
儿科
医学物理学
人工智能
病理
放射科
计算机科学
作者
William Rojas-Carabali,Carlos Cifuentes-González,Xin Wei,Ikhwanuliman Putera,Alok Sen,Zheng Xian Thng,Rajdeep Agrawal,Tobias Elze,Lucia Sobrin,John H. Kempen,Bernett Lee,Jyotirmay Biswas,Quan Dong Nguyen,Vishali Gupta,Alejandra de-la-Torre,Rupesh Agrawal
标识
DOI:10.1080/09273948.2023.2253471
摘要
Accurate diagnosis and timely management are vital for favorable uveitis outcomes. Artificial Intelligence (AI) holds promise in medical decision-making, particularly in ophthalmology. Yet, the diagnostic precision and management advice from AI-based uveitis chatbots lack assessment.We appraised diagnostic accuracy and management suggestions of an AI-based chatbot, ChatGPT, versus five uveitis-trained ophthalmologists, using 25 standard cases aligned with new Uveitis Nomenclature guidelines. Participants predicted likely diagnoses, two differentials, and next management steps. Comparative success rates were computed.Ophthalmologists excelled (60-92%) in likely diagnosis, exceeding AI (60%). Considering fully and partially accurate diagnoses, ophthalmologists achieved 76-100% success; AI attained 72%. Despite an 8% AI improvement, its overall performance lagged. Ophthalmologists and AI agreed on diagnosis in 48% cases, with 91.6% exhibiting concurrence in management plans.The study underscores AI chatbots' potential in uveitis diagnosis and management, indicating their value in reducing diagnostic errors. Further research is essential to enhance AI chatbot precision in diagnosis and recommendations.
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