The Comparison of ChatGPT 3.5, Microsoft Bing, and Google Gemini for Diagnosing Cases of Neuro-Ophthalmology

Ruchi Shukla; Ashutosh K Mishra; Nilakshi Banerjee; Archana Verma

doi:10.7759/cureus.58232

The Comparison of ChatGPT 3.5, Microsoft Bing, and Google Gemini for Diagnosing Cases of Neuro-Ophthalmology

Cureus. 2024 Apr 14;16(4):e58232. doi: 10.7759/cureus.58232. eCollection 2024 Apr.

Authors

Ruchi Shukla¹, Ashutosh K Mishra², Nilakshi Banerjee¹, Archana Verma²

Affiliations

¹ Department of Ophthalmology, All India Institute of Medical Sciences, Raebareli, Raebareli, IND.
² Department of Neurology, All India Institute of Medical Sciences, Raebareli, Raebareli, IND.

Abstract

Objective: We aim to compare the capabilities of ChatGPT 3.5, Microsoft Bing, and Google Gemini in handling neuro-ophthalmological case scenarios.

Methods: Ten randomly chosen neuro-ophthalmological cases from a publicly accessible database were used to test the accuracy and suitability of all three models, and the case details were followed by the following query: "What is the most probable diagnosis?"

Results: On the basis of the accuracy of diagnosis, all three chat boxes (ChatGPT 3.5, Microsoft Bing, and Google Gemini) gave the correct diagnosis in four (40%) out of 10 cases, whereas in terms of suitability, ChatGPT 3.5, Microsoft Bing, and Google Gemini gave six (60%), five (50%), and five (50%) out of 10 case scenarios, respectively.

Conclusion: ChatGPT 3.5 performs better than the other two when it comes to handling neuro-ophthalmological case difficulties. These results highlight the potential benefits of developing artificial intelligence (AI) models for improving medical education and ocular diagnostics.

Keywords: artificial intelligence; chatgpt; google gemini; microsoft bing; neuro-ophthalmology.