Related Experiment Video
Updated: May 8, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Evidence-based clinical decision support
1Yale Center for Medical Informatics, 300 George St., Ste 501, New Haven, CT 06511 USA.
Background:
Clinical decision support (CDS) is a key tool for enabling evidence-based medicine and improving the quality of healthcare. However, effective CDS faces a variety of challenges, including those relating to knowledge synthesis, capture, transformation, localization and maintenance. If not properly addressed, these challenges can limit the effectiveness of CDS, and potentially risk inaccurate or inappropriate interventions to clinicians.
Objectives:
(1) To describe an approach to CDS development using evidence as a basis for clinical decision support systems that promote effective care; (2) To review recent evidence regarding the effectiveness of selected clinical decision support systems.
Method:
Review and analysis of recent literature with identification of trends and best practices.
Results:
The state-of-the-art in CDS has advanced significantly, and many recent trials have shown CDS to be effective, although the results are mixed overall. Issues related to knowledge capture and synthesis, problems in knowledge transformation at the interface between knowledge authors and CDS developers, and problems specific to local CDS design and implementation can interfere with CDS development. Best practices, tools and techniques to manage them are described.
Conclusions:
CDS, when used well, can be effective, but further research is needed for it to reach its full potential.
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