Reasoning about Medical Triage Optimization with Logic Programming

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Authors: Jaikrishna Manojkumar Patil, Adam Chapman, Richard Knuszka, John W. Chapman, Paulo Shakarian
Cited by: 0

Abstract

We present a logic programming framework that orchestrates multiple variants of an optimization problem and reasons about their results to support high-stakes medical decision-making. The logic programming layer coordinates the construction and evaluation of multiple optimization formulations, translating solutions into logical facts that support further symbolic reasoning and ensure efficient resource allocation -- specifically targeting the "right patient, right platform, right escort, right time, right destination" principle. This capability is integrated into GuardianTwin, a decision support system for Forward Medical Evacuation (MEDEVAC), where rapid and explainable resource allocation is critical. Through a series of experiments, our framework demonstrates an average reduction in casualties by 35.75% compared to standard baselines. Additionally, we explore how users engage with the system via an intuitive interface that delivers explainable insights, ultimately enhancing decision-making in critical situations. This work demonstrates how logic programming can serve as a foundation for modular, interpretable, and operationally effective optimization in mission-critical domains.

Fields of Study & Subjects

Logic Reasoning and Knowledge AI-based Problem Solving and Planning Semantic Web and Ontologies

Publication details

Journal / source
Electronic Proceedings in Theoretical Computer Science
Volume
439
Pages
320–333
Publication date
8 January 2026
Language
EN