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

Camilo E Valderrama   1, 2, 3 , PhD ;   Daniel J Niven   4 , MD, PhD ;   Henry T Stelfox   3, 4 , MD, PhD ;   Joon Lee   1, 2, 3, 5 , PhD

1 Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada

2 Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada

3 O’Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada

4 Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada

5 Department of Cardiac Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada

Corresponding Author:

  • Camilo E Valderrama, PhD
  • Data Intelligence for Health Lab
  • Cumming School of Medicine
  • University of Calgary
  • 3280 Hospital Dr NW
  • Teaching, Research, & Wellness - TRW Building
  • Calgary, AB, T2N 4Z6
  • Canada
  • Phone: 1 403 220 8230
  • Email: camilo.valderramacua@ucalgary.ca