Challenge

From Data to Decisions:
Predicting the Future of Trauma Care
 

Year Three: Putting Predictive Algorithms to the Ultimate Test

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Over the past two years, teams from the Data Competition have used data from over 6,000 trauma center cases to train their predictive algorithms, developing robust predictions for need of life-saving interventions (LSIs). 

In the third year, we are challenging teams with the following tasks:

  • First look: Using the first five minutes of pre-hospital clinical procedures to make LSI predictions that may be needed hours later.
  • Continuous triage: As more in-hospital clinical data is presented, accurately predict LSIs needed in the next 20 minutes.
  • Resource prioritization: Scale LSI recommendations based on the availability of medical resources. This capability can help resource allocation planning in very large mass casualty incidents or in austere battlefield environments.

Teams

Qualified funded and unfunded teams participated in the competitions, striving to advance the use of autonomous systems for rapid, stand-off casualty assessment to facilitate timely and accurate medical triage.

 

Finals

AI TEMPO*

Michigan Technological University

AID3D Triage

Seraphim Triage

AUSTERE

University of Vermont

Coordinated Robotics*

Coordinated Robotics, USA

DBbun

DBbun LLC

The Disruptors

Disruptors

Engineering Dynamics

Engineering Dynamics

EverlignAI

EverlignAI

Kri Labs

Massachusetts Institute of Technology

STRETCH

MaXentric

MSALabs*

MarvsAI LTD

OCA-SENTINEL

Duke University

SunnyGoose

University of Toronto

Synthesis

Individual

Triage360

Omedus LLC


* DARPA-funded

See all teams | Team qualifications

Schedule

Finals | 2026

Workshop*March 27
Qualifications*June 28 - July 30
Competition*Sept. 30
Awards ceremonyNov. 14


* Submission deadline

darpa-challenge-dtc-data-competition
Source: DARPA | Jahyra Catala

Overview
 

Finals

2026

Competitions
Systems  |  Data

Challenge Event 2

2025

Competitions
Systems  |  Data

Challenge Event 1

2024

Competitions
Systems  |  Data |  Virtual

 

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