DEEPMED Search: An Open-Source Agentic Platform for Medical Deep Research with Introspective Verification
2026-06-29 • Artificial Intelligence
Artificial IntelligenceHuman-Computer Interaction
AI summaryⓘ
The authors created DEEPMED Search, an open-source tool to help researchers find trustworthy medical information from many sources like research articles and clinical guidelines. It smartly splits complicated questions into smaller parts and chooses the best place to search for each part. The tool also double-checks the facts it collects using a special system to avoid mistakes before giving a final, detailed report with references. This platform aims to make medical research more transparent and easier to do, especially for rare or complex diseases.
evidence-based medicinePubMedretrieval-augmented generation (RAG)Next.jsknowledge basesmulti-agent debatediagnostic logicrare diseasesopen-source softwaremedical information retrieval
Authors
Maolin Liu, Fanyu Xu, Ruoqing Xu, Jiahang Zhang, Hao Wang, Rui Wang
Abstract
Navigating the deluge of heterogeneous medical data, from academic literature (PubMed) to clinical guidelines (Web) and private knowledge bases, remains a critical bottleneck for evidence-based medicine. While commercial black-box tools lack transparency, standard open-source RAG implementations frequently suffer from reasoning drift when handling complex, long-tail queries. We present DEEPMED Search, a fully open-source, agentic platform designed for transparent medical deep research. Built on a high-performance Next.js architecture, DEEPMED Search features a source-adaptive router that autonomously dispatches sub-queries to PubMed, web search, or local graph-based knowledge bases based on information density. Crucially, the platform integrates an introspective verification module, powered by a causal-consistent multi-agent debate framework, to validate retrieved evidence against diagnostic logic before synthesis. To demonstrate its robustness, we showcase DEEPMED Search's ability to autonomously decompose high-difficulty rare disease queries, filter out confounding noise, and generate structured, citation-backed research reports in minutes. By open-sourcing this software, we provide the community with a robust infrastructure to democratize access to trustworthy, glass-box medical reasoning in research and prototyping settings.