Reasoning about Medical Triage Optimization with Logic Programming
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918278080757760 |
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| author | Patil, Jaikrishna Manojkumar Chapman, Adam Knuszka, Richard Chapman, John Shakarian, Paulo |
| author_facet | Patil, Jaikrishna Manojkumar Chapman, Adam Knuszka, Richard Chapman, John Shakarian, Paulo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_10781 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Reasoning about Medical Triage Optimization with Logic Programming Patil, Jaikrishna Manojkumar Chapman, Adam Knuszka, Richard Chapman, John Shakarian, Paulo Logic in Computer Science 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. |
| title | Reasoning about Medical Triage Optimization with Logic Programming |
| topic | Logic in Computer Science |
| url | https://arxiv.org/abs/2507.10781 |