Artificial intelligence and machine learning for early detection and diagnosis of colorectal cancer in sub-Saharan Africa

Authors

Akbar K. Waljee, Veterans Affairs Center for Clinical Management Research, USA
Eileen M. Weinheimer-Haus, University of Michigan, USA
Amina Abubakar, Aga Khan UniversityFollow
Anthony Ngugi, Aga Khan UniversityFollow
Geoffrey H. Siwo, University of Michigan, USA
Gifty Kwakye, University of Michigan, USA
Amit G. Singal, The University of Texas Southwestern Medical Center, USA
Arvind Rao, University of Michigan, USA
Christopher Opio, Aga Khan UniversityFollow
Mansoor Saleh, Aga Khan UniversityFollow

Document Type

Article

Department

Institute for Human Development; Population Health (East Africa); Internal Medicine (East Africa)

Publication (Name of Journal)

Gut

Recommended Citation

Waljee, A. K., Weinheimer-Haus, E. M., Abubakar, A., Ngugi, A., Siwo, G. H., Kwakye, G., Singal, A. G., Rao, A., Opio, C., Saleh, M. (2022). Artificial intelligence and machine learning for early detection and diagnosis of colorectal cancer in sub-Saharan Africa. Gut, 71(7), 1259-1265.
Available at: https://ecommons.aku.edu/eastafrica_ihd/145

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.