This paper is in the following e-collection/theme issue:

Clinical Informatics (1042) Clinical Information and Decision Making (1423) Decision Support for Health Professionals (1201) Machine Learning (1488)

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

Authors of this article:

Akram Mohammed1 Author Orcid Image ;   Pradeep S B Podila2 Author Orcid Image ;   Robert L Davis1 Author Orcid Image ;   Kenneth I Ataga3 Author Orcid Image ;   Jane S Hankins4 Author Orcid Image ;   Rishikesan Kamaleswaran5 Author Orcid Image
Article Authors Cited by (8) Tweetations (19) Metrics

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