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Updated: Oct 29, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
The Rare Knowledge Mining Methodological Framework for the Development of Practice Guidelines and Knowledge
C Gagnon1,2, J Fortin1, M E Lamontagne3,4
1Groupe de Recherche Interdisciplinaire sur les Maladies Neuromusculaires (GRIMN), Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay-Lac-Saint-Jean, Saguenay, Québec, Canada.
Abstract:
Rare diseases bring on a heavy health, social and economic burden that impacts patients' lives and puts pressure on the healthcare system. Furthermore, they are often associated with limited published studies to inform multidisciplinary clinical practice thus limiting evidence-based practice. Moreover, the development of knowledge translation products including clinical care guidelines are often very challenging based on the current available methodological frameworks relying mostly on critical appraisal of the published research evidence where randomized clinical trial design is considered as the gold standard. To overcome this barrier, we proposed the Rare Knowledge Mining Methodological Framework (RKMMF). The RKMMF is one possible answer to improve the development of knowledge translation products for rare diseases. This framework includes other sources of evidence including registry information and qualitative studies and the involvement of expert patients. This article documents the RKMMF structure and its application is exemplified through knowledge translation products developed for a neuromuscular population.
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