Article

Comparative Performance of agentic AI and Physicians in Taking Clinical History across Leading Large Language Models (LLMs)

2026-01-25

Abstract excerpt

<h4>ABSTRACT</h4> Comprehensive clinical history taking is essential for high-quality care. We hypothesized that large language models (LLMs), guided by a structured agentic framework, can efficiently obtain clinically meaningful patient histories. We developed an iterative prompting system that evaluates relevance and completeness across standard history domains and generates targeted follow-up questions until s...

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Literature Corpus work: a9bab6cb-3fd3-5613-9eeb-28d6f4c04a5a
DOI: 10.64898/2026.01.23.26344723

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