Predictive Algorithms and Learning for Combat Medics (PAL-MEDIC)

Elan Freedy1, Ross Donaldson2, Gersh Weltman3, William Rand4, Sara Mastro3, James Ross5

  • 1Perceptronics Solutions, Inc
  • 2Critical Innovations LLC
  • 3Perceptronics
  • 4North Carolina State University
  • 5Oregon Health & Science University

Details

Category

1-Page Technical Papers (Poster)

Sessions

12:00 - 14:00 | Tue 7 Nov | Auditorium Foyer, E1/E2, Upper Atrium Space | TPO

Lunch, Posters and POC Technologies Demonstrations – Session II

Abstract

PAL-MEDIC is a mobile decision support tool that supports combat medics in providing pre-hospital care based on Tactical Combat Casualty Care (TC3) guidelines. The core technical elements of PAL-MEDIC are: (a) predictive algorithms and machine learning that can predict a deterioration in patient status, and (b) adaptive protocols for care recommendation based on decision tree representations of TC3 protocols. This paper summarizes the result of our initial proof of concept and current development on a complete prototype.

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