Remote triage support algorithm based on fuzzy logic.

Area of Science:

• Military Medicine
• Biomedical Engineering
• Artificial Intelligence in Healthcare

Background:

• Continuous monitoring of soldiers' vital signs is crucial for timely medical intervention.
• Existing telemedicine systems require integration with advanced decision-support tools for efficient casualty management.

Purpose of the Study:

• To develop and validate a remote triage support algorithm for a military telemedicine system.
• To assess the algorithm's performance in classifying casualty health risks using physiological data.

Main Methods:

• A fuzzy logic-based algorithm was developed to process vital sign data.
• The algorithm calculates health risk levels based on the Modified Early Warning Score (MEWS) methodology.
• Algorithm performance was evaluated against 50 experienced physicians using simulated scenarios.

Main Results:

• The algorithm demonstrated a high average correlation (0.928) with expert medical assessments.
• Eight different evaluation scenarios confirmed the algorithm's classification accuracy.
• Computational efficiency was improved in a subsequent study without sacrificing classification quality.

Conclusions:

• The proposed algorithm facilitates automated remote triage, potentially saving lives by shortening response times.
• It can be deployed in real-time, life-saving situations prior to medical team arrival.
• The algorithm offers a reliable tool for enhancing battlefield medical support.