Multimodal reasoning agent for enhanced ophthalmic decision-making: a preliminary real-world clinical validation

Abstract

< 0.05). While GPT-4o showed vulnerabilities in rare cases (90.48% low diagnostic scores), ReasonAgent's hybrid design mitigated errors through structured reasoning. Statistical analysis identified significant case-level heterogeneity (diagnosis ICC = 0.28), highlighting the need for domain-specific AI solutions in complex clinical contexts. This framework establishes a novel paradigm for domain-specific AI in real-world clinical practice, demonstrating the potential of modularized architectures to advance decision fidelity through human-aligned reasoning pathways.

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