Refinement of an Artificial Intelligence Algorithm for Enhanced Burn Wound Depth Assessment Using Multispectral Imaging: An Expanded Proof of Concept Study
An optimal CNN architecture and the importance of "time-since-injury" as a covariate were identified, informing the design/powering of upcoming algorithm training and validation studies.
Authors
- Clay J. Cockerell (ORCID: https://orcid.org/0000-0001-7125-0283)
- Jeffrey W. Shupp (ORCID: https://orcid.org/0000-0002-4394-6416)
- William L. Hickerson (ORCID: https://orcid.org/0009-0009-1817-4002)
- Jeffrey E Carter (ORCID: https://orcid.org/0000-0002-8777-6762)
- John Michael DiMaio (ORCID: https://orcid.org/0000-0002-6064-5869)
- James H. Holmes (ORCID: https://orcid.org/0000-0002-3850-9406)
- Herb A. Phelan
Institutions
- Atrium Health Wake Forest Baptist (US)
- University of New Orleans (US)
- University Medical Center New Orleans (US)
- ProMedica Charles and Virginia Hickman Hospital (US)
- Propath Services (United States) (US)
- Dermatology Specialists (US)
- Louisiana State University Health Sciences Center New Orleans (US)
- MedStar Health (US)
Publication Details
- Journal
- Journal of Burn Care & Research
- Published
- 2025-05-29
- DOI
- https://doi.org/10.1093/jbcr/iraf057
- Citations
- 2
- Primary Topic
- Optical Imaging and Spectroscopy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.72