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Updated: Apr 7, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system
Ying Shen1, Joël Colloc2, Armelle Jacquet-Andrieu3
1Peking University Shenzhen Graduate School - Institute of Big Data Technologies, School of Electronics and Computer Engineering (SECE), Shenzhen Key Lab for Cloud Computing Technology & Applications, PKU Shenzhen Graduate School, 518055 Shenzhen, PR China; Université Paris Ouest (UMR CNRS 7114) - MoDyCo, 200 avenue de la République, 92000 Nanterre, France.
Abstract:
This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts.
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