Published on in Vol 22, No 5 (2020): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14693, first published .
Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study

Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study

Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study

Akram Mohammed   1 , PhD ;   Pradeep S B Podila   2 , PhD, MHA, MS ;   Robert L Davis   1 , MD, MPH ;   Kenneth I Ataga   3 , MD ;   Jane S Hankins   4 , MD, MS ;   Rishikesan Kamaleswaran   5 , PhD

1 Center for Biomedical Informatics, University of Tennessee Health Science Center, Memphis, TN, United States

2 Faith and Health Division, Methodist Le Bonheur Healthcare, Memphis, TN, United States

3 Center for Sickle Cell Disease, University of Tennessee Health Science Center, Memphis, TN, United States

4 Department of Hematology, St Jude Children's Research Hospital, Memphis, TN, United States

5 Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, United States

Corresponding Author:

  • Rishikesan Kamaleswaran, PhD
  • Department of Biomedical Informatics
  • Emory University School of Medicine
  • WMB, 101 Woodruff Circle, Suite 4127
  • Atlanta, GA, 30322
  • United States
  • Phone: 1 (901) 462-6908
  • Email: rkamaleswaran@emory.edu