Refinement of machine learning arterial waveform models for predicting blood loss in canines
ML methods successfully tracked hemorrhage and provided earlier prediction in canines, potentially improving hemorrhage detection and objectifying triage for veterinary medicine. Further, its use can potentially be extended to human use with proper training datasets.
Authors
- Thomas H. Edwards (ORCID: https://orcid.org/0000-0002-1706-9536)
- Guillaume L. Hoareau (ORCID: https://orcid.org/0000-0002-8635-3960)
- Jose M. Gonzalez (ORCID: https://orcid.org/0000-0002-4325-409X)
- Eric J. Snider (ORCID: https://orcid.org/0000-0002-0293-4937)
Institutions
- University of Utah (US)
- United States Army Institute of Surgical Research (US)
- Texas A&M University (US)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2024-08-21
- DOI
- https://doi.org/10.3389/frai.2024.1408029
- Citations
- 5
- Primary Topic
- Trauma, Hemostasis, Coagulopathy, Resuscitation
- Type
- article
- Field-Weighted Citation Impact
- 2.11
Funders
- U.S. Department of Defense