VQV Signal
The clinical-evidence-navigator is a full-stack agentic retrieval-augmented generation (RAG) system that uses LLM reasoning to match patient profiles to oncology clinical trials on ClinicalTrials.gov. It provides citation-backed outputs and includes an abstention policy for low confidence matches.
The clinical-evidence-navigator is a full-stack agentic retrieval-augmented generation (RAG) system that uses LLM reasoning to match patient profiles to oncology clinical trials on ClinicalTrials.gov. It provides citation-backed outputs and includes an abstention policy for low confidence matches.
AI-assisted summary based on the listed source.
Full-stack agentic RAG system (Next.js, FastAPI, pgvector) that matches patient profiles to oncology clinical trials via criterion by criterion LLM reasoning over ClinicalTrials.gov with citation backed outputs and a built in abstention policy for low confidence matches. Stars: 1. Updated repository signal.
This system enhances precision in matching patients to relevant clinical trials by reasoning over trial criteria with large language models, potentially improving trial enrollment and patient outcomes. The built-in abstention policy helps maintain reliability by avoiding uncertain matches.
VQV organizes public signals from inspectable sources. It does not independently verify the underlying report.
Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.
VQV surfaced this signal because it is recent, relevant to AI Search, connected to GitHub.
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