mlsanityData to 14 Oct 2026

Streamlining evidence based clinical recommendations with large language models

arXiv 2505.10282 ↗First posted 15 May 2025cs.CL cs.AIcited by 3

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Abstract (arXiv)

Clinical evidence underpins informed healthcare decisions, yet integrating it into real-time practice remains challenging due to intensive workloads, complex procedures, and time constraints. This study presents Quicker, an LLM-powered system that automates evidence synthesis and generates clinical recommendations following standard guideline development workflows. Quicker delivers an end-to-end pipeline from clinical questions to recommendations and supports customized decision-making through integrated tools and interactive interfaces. To evaluate how closely Quicker can reproduce guideline development processes, we constructed Q2CRBench-3, a benchmark derived from guideline development records for three diseases. Experiments show that Quicker produces precise question decomposition, expert-aligned retrieval, and near-comprehensive screening. Quicker assistance improved the accuracy of extracted study data, and its recommendations were more comprehensive and coherent than clinician-written ones. In system-level testing, Quicker working with one participant reduced recommendation development to 20-40 min. Overall, the findings demonstrate Quicker's potential to enhance the speed and reliability of evidence-based clinical decision-making.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 16 of its 77 references that are in the map. First posted on arXiv 15 May 2025.

Builds on

16 of 77 references.

References · 16

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4 more
  1. 2024In-Context Principle Learning from Mistakescited by 44
  2. 2024ConStat: Performance-Based Contamination Detection in Large Language Modelscited by 33
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2025MedBayes-Lite: A Clinical Uncertainty Governance Layer for Risk-Aware Medical Decision Supportcited by 1
  2. 2026A Multi-Stage Validation Framework for Trustworthy Large-scale Clinical Information Extraction using Large Language Modelscited by 0
  3. 2026Human-LLM Dialogue Improves Diagnostic Accuracy in Emergency Carecited by 0