HealthFlow: A Self-Evolving AI Agent with Meta Planning for Autonomous Healthcare Research
- URL: http://arxiv.org/abs/2508.02621v1
- Date: Mon, 04 Aug 2025 17:08:47 GMT
- Title: HealthFlow: A Self-Evolving AI Agent with Meta Planning for Autonomous Healthcare Research
- Authors: Yinghao Zhu, Yifan Qi, Zixiang Wang, Lei Gu, Dehao Sui, Haoran Hu, Xichen Zhang, Ziyi He, Liantao Ma, Lequan Yu,
- Abstract summary: We introduce HealthFlow, a self-evolving AI agent that overcomes limitations through a novel meta-level evolution mechanism.<n>HealthFlow autonomously refines its own high-level problem-solving policies by distilling procedural successes and failures into a durable, strategic knowledge base.<n>Our experiments demonstrate that HealthFlow's self-evolving approach significantly outperforms state-of-the-art agent frameworks.
- Score: 16.963151914975438
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The efficacy of AI agents in healthcare research is hindered by their reliance on static, predefined strategies. This creates a critical limitation: agents can become better tool-users but cannot learn to become better strategic planners, a crucial skill for complex domains like healthcare. We introduce HealthFlow, a self-evolving AI agent that overcomes this limitation through a novel meta-level evolution mechanism. HealthFlow autonomously refines its own high-level problem-solving policies by distilling procedural successes and failures into a durable, strategic knowledge base. To anchor our research and facilitate reproducible evaluation, we introduce EHRFlowBench, a new benchmark featuring complex, realistic health data analysis tasks derived from peer-reviewed clinical research. Our comprehensive experiments demonstrate that HealthFlow's self-evolving approach significantly outperforms state-of-the-art agent frameworks. This work marks a necessary shift from building better tool-users to designing smarter, self-evolving task-managers, paving the way for more autonomous and effective AI for scientific discovery.
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