Predicting blood loss volume in a canine model of hemorrhagic shock using arterial waveform machine learning analysis
Canine BLVM may be useful in estimating blood loss in dogs, which can guide resuscitation strategies for these patients.
Authors
- Lawrence Holland (ORCID: https://orcid.org/0000-0003-0210-6856)
- Sofía I. Hernández Torres (ORCID: https://orcid.org/0000-0002-0764-519X)
- Thomas H. Edwards (ORCID: https://orcid.org/0000-0002-1706-9536)
- Nicole Ewer
- Guillaume L. Hoareau (ORCID: https://orcid.org/0000-0002-8635-3960)
- Rebekah Ford
- Emilee C. Venn (ORCID: https://orcid.org/0000-0002-9158-1677)
- Jose M. Gonzalez (ORCID: https://orcid.org/0000-0002-4325-409X)
- Eric J. Snider (ORCID: https://orcid.org/0000-0002-0293-4937)
- Victor A. Convertino (ORCID: https://orcid.org/0000-0003-4627-136X)
Institutions
- Uniformed Services University of the Health Sciences (US)
- The University of Texas at San Antonio Health Science Center (US)
- University of Utah (US)
- United States Army Institute of Surgical Research (US)
- Joint Base San Antonio (US)
- Texas A&M University (US)
Publication Details
- Journal
- American Journal of Veterinary Research
- Published
- 2024-12-11
- DOI
- https://doi.org/10.2460/ajvr.24.09.0256
- Citations
- 1
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.18
Funders
- U.S. Department of Defense
- U.S. Department of Energy
- Oak Ridge Associated Universities
- National Institutes of Health
- Oak Ridge Institute for Science and Education