RAG for UK NICE guidelines: high-recall retrieval and near-perfect faithfulness

Kari Jaaskelainen

06 Oct 2025

From pages to precise answers. 🏥🔎📚✅

This system queries UK NICE clinical guidelines with a hybrid retrieval stack over 10,195 chunks (from 300 guidelines). On 7,901 queries: MRR 0.814; Recall 81%@1 and 99.1%@10. In generation on 70 QA pairs, RAG-enhanced models achieved perfect context precision (1) and boosted faithfulness—e.g., O4-Mini to 99.5%—far above a compared baseline (43%).

Why it matters: Grounded answers reduce hallucinations and speed evidence access—key in time-pressed care.

Evidence in, errors out. Share with your clinical AI team.

Paper: http://arxiv.org/abs/2510.02967v1
Register: https://www.AiFeta.com

Paper: http://arxiv.org/abs/2510.02967v1

Register: https://www.AiFeta.com

#RAG #HealthcareAI #NICEGuidelines #EvidenceBased #LLM #Retrieval #MedicalInformatics #Faithfulness

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