Work

Non-Expert Markings of Active Chronic Graft-Versus-Host Disease Photographs: Optimal Metrics of Training Effects

Year: 2022

Type: article

Source: Journal of Imaging Informatics in Medicine

DOI: 10.1007/s10278-022-00730-8

Authors: Kelsey Parks, Xiaoqi Liu, Tahsin Reasat, Zain Khera, Laura X. Baker, Heidi Chen, Benoit M. Dawant, Inga Saknite, Eric R. Tkaczyk

Institutions: VA Tennessee Valley Healthcare System, Vanderbilt University Medical Center, Vanderbilt University, University of Latvia

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: U.S. Department of Veterans Affairs, National Institutes of Health, European Regional Development Fund, National Cancer Institute, National Institute of Arthritis and Musculoskeletal and Skin Diseases

Awards: Automatic analysis of 3D skin images for chronic graft-versus-host disease (cGVHD) severity assessment, G2053920163, G306019702, Vanderbilt Clinical Oncology Research Career Development Award

OpenAlex ID: W4308404169

FWCI: 0.161

Cites: 27

Cited by: 4

Related to: 10