Related Experiment Video
Updated: Jun 28, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Knowledge representation of critical laboratory results in using the SAGE framework and challenges to its
Jae Hyun Lee1, In Sook Cho, Kyoung Un Park
1R&D Center for interoperable EHR, Seoul, Korea.
Abstract:
When a laboratory result is abnormal, the Computerized Critical Laboratory Results Alerting System should notify clinicians promptly. Use of this system can decrease the length of time spent in life-threatening situations, the average length of stay and the cost. 10 criteria oriented not to the individual but to a large number of patients were defined, these criteria were encoded using the SAGE framework. This type of modeling is utilized to validate a knowledge converter that converts the SAGE output to a knowledge engine.
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