eJHaem
(May 2021)
Using machine learning to predict rapid decline of kidney function in sickle cell anemia
- Fatma Güntürkün,
- Daiqing Chen,
- Oguz Akbilgic,
- Robert L. Davis,
- Ibrahim Karabayir,
- Maxwell Strome,
- Yang Dai,
- Santosh L. Saraf,
- Kenneth I. Ataga
Affiliations
- Fatma Güntürkün
- Center for Biomedical Informatics University of Tennessee Health Science Center Memphis USA
- Daiqing Chen
- Department of Bioengineering University of Illinois at Chicago Chicago USA
- Oguz Akbilgic
- Department of Health Informatics and Data Science Loyola University Chicago Maywood USA
- Robert L. Davis
- Center for Biomedical Informatics University of Tennessee Health Science Center Memphis USA
- Ibrahim Karabayir
- Department of Health Informatics and Data Science Loyola University Chicago Maywood USA
- Maxwell Strome
- Department of Computer Science University of Michigan Ann Arbor USA
- Yang Dai
- Department of Bioengineering University of Illinois at Chicago Chicago USA
- Santosh L. Saraf
- Department of Medicine University of Illinois at Chicago Chicago USA
- Kenneth I. Ataga
- Center for Sickle Cell Disease University of Tennessee Health Science Center Memphis USA
- DOI
-
https://doi.org/10.1002/jha2.168
- Journal volume & issue
-
Vol. 2,
no. 2
pp.
257
– 260
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