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

Machine Learning (1400) Decision Support for Health Professionals (1145) Electronic Health Records (971) Intensive Care Unit (ICU) (102)

Published on in Vol 10, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35250, first published .
Predicting Abnormal Laboratory Blood Test Results in the Intensive Care Unit Using Novel Features Based on Information Theory and Historical Conditional Probability: Observational Study

Predicting Abnormal Laboratory Blood Test Results in the Intensive Care Unit Using Novel Features Based on Information Theory and Historical Conditional Probability: Observational Study

Predicting Abnormal Laboratory Blood Test Results in the Intensive Care Unit Using Novel Features Based on Information Theory and Historical Conditional Probability: Observational Study

Authors of this article:

Camilo E Valderrama1, 2, 3 Author Orcid Image ;   Daniel J Niven4 Author Orcid Image ;   Henry T Stelfox3, 4 Author Orcid Image ;   Joon Lee1, 2, 3, 5 Author Orcid Image
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