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Comparative evaluation demonstrates language models excel in data synthesis but struggle with nuanced diagnoses in nephrology.
This study evaluates the dynamic clinical reasoning of 4 leading large language models in complex nephrology cases, demonstrating that while Gemini 2.5 Pro achieved the highest reasoning scores and computational efficiency, all tested models excelled at static data synthesis but shared vulnerabilities in formulating nuanced differential diagnoses and in prospective clinical planning.
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Yano et al. (2026) studied this question.
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