A new retinal-imaging multimodal dataset and an ophthalmology-specific reasoning model claim state-of-the-art gains of 15 to 25 percent over existing medical and general multimodal LLMs.
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Bridging the Gap in Ophthalmic AI: MM-Retinal-Reason Dataset and OphthaReason Model toward Dynamic Multimodal Reasoning
A new retinal-imaging multimodal dataset and an ophthalmology-specific reasoning model claim state-of-the-art gains of 15 to 25 percent over existing medical and general multimodal LLMs.