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

Machine Learning (1501) Clinical Informatics (1050) Clinical Information and Decision Making (1434) Big Data (245) Decision Support for Health Professionals (1210) Electronic Health Records (1068)

Published on in Vol 5, No 1 (2017): Jan-Mar

Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill

Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill

Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill

Authors of this article:

Joon Lee1 Author Orcid Image
Article Authors Cited by (23) Tweetations (7) Metrics

Joon Lee   1 , PhD

1 Health Data Science Lab, School of Public Health and Health Systems, University of Waterloo, Waterloo, ON, Canada

Corresponding Author:

  • Joon Lee, PhD
  • Health Data Science Lab
  • School of Public Health and Health Systems
  • University of Waterloo
  • 200 University Ave W
  • Waterloo, ON, N2L 3G1
  • Canada
  • Phone: 1 519 888 4567 ext 31567
  • Fax: 1 519 746 6776
  • Email: joon.lee@uwaterloo.ca