Multi-agent system does fine-tuning-free clinical symptom detection from unstructured notes

arXiv·medium signal

A new arXiv paper (2607.12886) presents and validates a multi-agent system that extracts signs and symptoms from free-text clinical notes without any task-specific fine-tuning, surfacing information that rarely reaches structured fields. It's a concrete production pattern for multi-agent extraction over messy, domain-specific documents — coordinating LLM agents instead of training a bespoke model — with a development-and-validation study rather than a toy benchmark. Relevant to builders applying agent orchestration to regulated, high-stakes document domains.