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Evaluating the Diagnostic Accuracy and Management Recommendations of ChatGPT in Uveitis.
Rojas-Carabali, William; Cifuentes-González, Carlos; Wei, Xin; Putera, Ikhwanuliman; Sen, Alok; Thng, Zheng Xian; Agrawal, Rajdeep; Elze, Tobias; Sobrin, Lucia; Kempen, John H; Lee, Bernett; Biswas, Jyotirmay; Nguyen, Quan Dong; Gupta, Vishali; de-la-Torre, Alejandra; Agrawal, Rupesh.
Affiliation
  • Rojas-Carabali W; National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore, Singapore.
  • Cifuentes-González C; Department of Bioinformatics, Lee Kong Chiang School of Medicine, Nanyang Technological University, Singapore, Singapore.
  • Wei X; Neuroscience Research Group (NEUROS), Neurovitae Center for Neuroscience, Institute of Translational Medicine (IMT), Escuela de Medicina y Ciencias de la Salud, Universidad del Rosario, Bogotá, Colombia.
  • Putera I; National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore, Singapore.
  • Sen A; Department of Ophthalmology, Faculty of Medicine Universitas Indonesia - CiptoMangunkusmoKirana Eye Hospital, Jakarta, Indonesia.
  • Thng ZX; Laboratory Medical Immunology, Department of Immunology, ErasmusMC, University Medical Centre, Rotterdam, the Netherlands.
  • Agrawal R; Department of Internal Medicine, Division of Clinical Immunology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
  • Elze T; Department of Ophthalmology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
  • Sobrin L; Department of Vitreoretina and Uveitis, Sadguru Netra Chikatsalya, Chitrakoot, India.
  • Kempen JH; National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore, Singapore.
  • Lee B; Department of Bioinformatics, Lee Kong Chiang School of Medicine, Nanyang Technological University, Singapore, Singapore.
  • Biswas J; Department of Ophthalmology, Massachusetts Eye and Ear/Harvard Medical School, and Schepens Eye Research Institute, Boston, Massachusetts, USA.
  • Nguyen QD; Department of Ophthalmology, Massachusetts Eye and Ear/Harvard Medical School, and Schepens Eye Research Institute, Boston, Massachusetts, USA.
  • Gupta V; Department of Ophthalmology, Massachusetts Eye and Ear/Harvard Medical School, and Schepens Eye Research Institute, Boston, Massachusetts, USA.
  • de-la-Torre A; Community Ophthalmology, Sight for Souls, Bellevue, Washington, USA.
  • Agrawal R; Department of Ophthalmology, Addis Ababa University, Addis Ababa, Ethiopia.
Ocul Immunol Inflamm ; : 1-6, 2023 Sep 18.
Article in En | MEDLINE | ID: mdl-37722842
INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Guideline / Prognostic_studies Language: En Journal: Ocul Immunol Inflamm Journal subject: ALERGIA E IMUNOLOGIA / OFTALMOLOGIA Year: 2023 Document type: Article Affiliation country: Singapore Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Guideline / Prognostic_studies Language: En Journal: Ocul Immunol Inflamm Journal subject: ALERGIA E IMUNOLOGIA / OFTALMOLOGIA Year: 2023 Document type: Article Affiliation country: Singapore Country of publication: United kingdom