RETINAL IMAGING ANALYSIS PERFORMED BY CHATGPT-4o AND GEMINI ADVANCED

Abstract

PURPOSE: To assess the diagnostic capabilities of the most recent chatbots releases, GPT-4o and Gemini Advanced, facing different retinal diseases. METHODS: Exploratory analysis on 50 cases with different surgical (n = 27) and medical (n = 23) retinal pathologies, whose optical coherence tomography/angiography scans were dragged into ChatGPT and Gemini's interfaces. Then, the authors asked "Please describe this image" and classified the diagnosis as: 1) Correct; 2) Partially correct; 3) Wrong; 4) Unable to assess exam type; and 5) Diagnosis not given. RESULTS: ChatGPT indicated the correct diagnosis in 31 of 50 cases (62%), significantly higher than Gemini Advanced in 16 of 50 cases ( P = 0.0048). In 24% of cases, Gemini Advanced was not able to produce any answer, stating "That's not something I'm able to do yet." For both, primary misdiagnosis was macular edema, given erroneously in 16% and 14% of cases, respectively. ChatGPT-4o showed higher rates of correct diagnoses either in surgical (52% vs. 30%) or in medical retina (78% vs. 43%). Notably, when presented without the corresponding structural image, in any case Gemini was able to recognize optical coherence tomography angiography scans, confusing images for artworks. CONCLUSION: ChatGPT-4o outperformed Gemini Advanced in diagnostic accuracy facing optical coherence tomography/angiography images, even if the range of diagnoses is still limited.

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