Enhancing Diagnostic Accuracy of Ophthalmological Conditions with Complex Prompts in GPT-4: A Comparative Analysis of Global and LMIC-Specific Pathologies (dataset)

Ten clinical vignettes representing globally and LMIC-prevalent ophthalmological conditions were presented to GPT-4-0125-preview using simple and complex prompts. Diagnostic performance metrics, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were calculated. Statistical comparison between prompts was conducted using a Chi-Square Test of Independence.