Knee arthritis severity measurement using deep learning: a publicly available algorithm with a multi-institutional validation showing radiologist-level performance
Publication
, Preprint
Gu, H; Li, K; Colglazier, RJ; Yang, J; Lebhar, M; O'Donnell, J; Jiranek, WA; Mather, RC; French, RJ; Said, N; Zhang, J; Park, C; Mazurowski, MA
March 16, 2022
Duke Scholars
Publication Date
March 16, 2022
Citation
APA
Chicago
ICMJE
MLA
NLM
Gu, H., Li, K., Colglazier, R. J., Yang, J., Lebhar, M., O’Donnell, J., … Mazurowski, M. A. (2022). Knee arthritis severity measurement using deep learning: a publicly available algorithm with a multi-institutional validation showing radiologist-level performance.
Gu, Hanxue, Keyu Li, Roy J. Colglazier, Jichen Yang, Michael Lebhar, Jonathan O’Donnell, William A. Jiranek, et al. “Knee arthritis severity measurement using deep learning: a publicly available algorithm with a multi-institutional validation showing radiologist-level performance,” March 16, 2022.
Gu H, Li K, Colglazier RJ, Yang J, Lebhar M, O’Donnell J, et al. Knee arthritis severity measurement using deep learning: a publicly available algorithm with a multi-institutional validation showing radiologist-level performance. 2022.
Gu H, Li K, Colglazier RJ, Yang J, Lebhar M, O’Donnell J, Jiranek WA, Mather RC, French RJ, Said N, Zhang J, Park C, Mazurowski MA. Knee arthritis severity measurement using deep learning: a publicly available algorithm with a multi-institutional validation showing radiologist-level performance. 2022.
Publication Date
March 16, 2022