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Updated: Jun 4, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Integrating heterogeneous knowledge sources to acquire executable drug-related knowledge
Xiaoyan Wang1, Herbert S Chase, Jianhua Li
1Department of Biomedical Informatics, Columbia University, New York, NY.
Abstract:
Knowledge of medical entities, such as drug-related information is critical for many automated biomedical applications, such as decision support and pharmacovigilance. In this work, heterogeneous information sources were integrated automatically to obtain drug-related knowledge. We focus on one type of knowledge, drug-treats-condition, in the study and propose a framework for integrating disparate knowledge sources. Evaluation based on a random sample of drug-condition pairs indicated an overall coverage of 96%, recall of 98% and a precision of 87%. In conclusion, the preliminary study demonstrated that the knowledge generated from this study was comparable to the manually curated gold standard and that this method of automatically integrating knowledge sources is effective. The automated method should also be applicable to integrate other clinical knowledge, such as drug-related knowledge with omics information.
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