Singly-Connected Multiple Minimal Networks for Efficient Temporal Reasoning About Multiple Clinical Guideline Instantiations
Singly-Connected Multiple Minimal Networks for Efficient Temporal Reasoning About Multiple Clinical Guideline Instantiations
Andrea Terenziani
Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence
AI and Health. Pages 6904-6912.
https://doi.org/10.24963/ijcai.2026/768
Temporal constraints are an intrinsic component of most clinical guidelines. Several approaches to computerized clinical guidelines (CIGs) offer temporal reasoning facilities to support the execution of a CIG for a specific patient, mostly based on bounds on differences and on the Simple Temporal Problem framework. However, in scheduling activities (e.g., within a hospital), it is necessary to consider multiple executions of CIGs for different patients, which can also be (partly) related to each other. In this work we extend current temporal reasoning techniques to apply to such a context. We propose a new temporal constraint model, prove its properties, and exploit them to provide efficient management of patients' temporal constraints, and to support efficient query answering. We also propose an experimental evaluation, demonstrating the step forward with respect to current approaches. Notably, our approach is general, and can apply to all temporal reasoning problems having the same topology of the "multiple CIG execution" problem.
Keywords:
Automated reasoning in clinical domains: Automated reasoning in clinical domains
Medical knowledge representation: Medical knowledge representation
