Tehran University of Medical Sciences

Science Communicator Platform

Share By
Performance of Chatgpt in Diagnosis of Corneal Eye Diseases Publisher Pubmed

Summary: Can AI diagnose eye diseases? Study finds ChatGPT-4.0 reaches 85% accuracy for corneal conditions. #CornealDisease #ChatGPT

Delsoz M1 ; Madadi Y1 ; Raja H1 ; Munir WM2 ; Tamm B2 ; Mehravaran S3 ; Soleimani M4, 5 ; Djalilian A4 ; Yousefi S1, 6
Authors

Source: Cornea Published:2024


Abstract

Purpose:The aim of this study was to assess the capabilities of ChatGPT-4.0 and ChatGPT-3.5 for diagnosing corneal eye diseases based on case reports and compare with human experts.Methods:We randomly selected 20 cases of corneal diseases including corneal infections, dystrophies, and degenerations from a publicly accessible online database from the University of Iowa. We then input the text of each case description into ChatGPT-4.0 and ChatGPT-3.5 and asked for a provisional diagnosis. We finally evaluated the responses based on the correct diagnoses, compared them with the diagnoses made by 3 corneal specialists (human experts), and evaluated interobserver agreements.Results:The provisional diagnosis accuracy based on ChatGPT-4.0 was 85% (17 correct of 20 cases), whereas the accuracy of ChatGPT-3.5 was 60% (12 correct cases of 20). The accuracy of 3 corneal specialists compared with ChatGPT-4.0 and ChatGPT-3.5 was 100% (20 cases, P = 0.23, P = 0.0033), 90% (18 cases, P = 0.99, P = 0.6), and 90% (18 cases, P = 0.99, P = 0.6), respectively. The interobserver agreement between ChatGPT-4.0 and ChatGPT-3.5 was 65% (13 cases), whereas the interobserver agreement between ChatGPT-4.0 and 3 corneal specialists was 85% (17 cases), 80% (16 cases), and 75% (15 cases), respectively. However, the interobserver agreement between ChatGPT-3.5 and each of 3 corneal specialists was 60% (12 cases).Conclusions:The accuracy of ChatGPT-4.0 in diagnosing patients with various corneal conditions was markedly improved than ChatGPT-3.5 and promising for potential clinical integration. A balanced approach that combines artificial intelligence-generated insights with clinical expertise holds a key role for unveiling its full potential in eye care. © 2024 Lippincott Williams and Wilkins. All rights reserved.
Performance of Chatgpt in Diagnosis of Corneal Eye Diseases