Accession Number:

AD1105924

Title:

The Burn Medical Assistant: Developing Machine Learning Algorithms to Aid in the Estimation of Burn Wound Size (BURNMAN)

Personal Author(s):

Corporate Author:

U.S. Army Institute of Surgical Research (USAISR) San Antonio United States

Report Date:

2020-01-01

Abstract:

The American Burn Association reports that roughly 450,000 patients receive hospital and emergency room treatment for burns each year, and of these patients, roughly 3,400 burn injury deaths occur. According to the Centers for Disease Control and Prevention CDC, burns and fires are the third leading cause of death in the home. Thermal injuries occur in approximately 10 of combat trauma. Mortality rates for these patients remains high, half of casualties with 60-70 Total Body Surface Area TBSA burns die, whereas in civilian centers, roughly 50 of similarly matched patients with an 80 TBSA die. Since battlefield resources are inherently limited, triage is essential to determining the appropriate resources to be applied, and this is especially relevant to thermal injuries. It is critical for the medic on the battlefield to be able to make a rapid,accurate assessment of burn severity for triage, resuscitation, and evacuation planning purposes. But an error on the battlefield in estimating burn severity of over 10 can result in medics spending resources on unrecoverable patients at the expense of recoverable patients, or providing expectant care to a patient who could otherwise be saved.

Descriptive Note:

Technical Report,01 Oct 2016,30 Sep 2019

Pages:

0045

Descriptors:

Subject Categories:

Communities Of Interest:

Modernization Areas:

Distribution Statement:

Approved For Public Release;

File Size:

1.99MB

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