SOURCE-LINKED INTELLIGENCE

ClinAgent: A ReAct-Based Agent for Conversational Access to Clinical Trial Information

arXiv · AI, language, vision and robotics · article · Sep 12, 2026 · UTC

Querying clinical trial registries remains a manual and error-prone process, requiring researchers to navigate large volumes of semi-structured data without support for natural language interaction or cross-source synthesis. To address this, we introduce ClinAgent, a conversational system based on agentic Retrieval-Augmented Generation (RAG) that enables clinicians and researchers to query clinical trial information in plain language and receive grounded, up-to-date responses across multi-turn interactions. The system centers on a Large Language Model (LLM) agent following the ReAct paradigm,

Read original source ↗ Open in workspace

recordType

paper

region

Global