Published on in Vol 23, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25187, first published .
Machine Learning–Based Early Warning Systems for Clinical Deterioration: Systematic Scoping Review

Machine Learning–Based Early Warning Systems for Clinical Deterioration: Systematic Scoping Review

Machine Learning–Based Early Warning Systems for Clinical Deterioration: Systematic Scoping Review

Sankavi Muralitharan 1, 2, MPharm, MSc;  Walter Nelson 1*, BSc;  Shuang Di 1, 3*, BSc, MEd, MSc;  Michael McGillion 4, 5, BScN, PhD;  PJ Devereaux 4, 6, MD, PhD, FRCPC;  Neil Grant Barr 7, BA, MSc, PhD;  Jeremy Petch 1, 4, 8, 9, HBA, MA, PhD

1 Centre for Data Science and Digital Health, Hamilton Health Sciences , Hamilton, ON, CA

2 DeGroote School of Business, McMaster University , Hamilton, ON, CA

3 Dalla Lana School of Public Health, University of Toronto , Toronto, ON, CA

4 Population Health Research Institute , Hamilton, ON, CA

5 School of Nursing, McMaster University , Hamilton, ON, CA

6 Departments of Health Evidence and Impact and Medicine, McMaster University , Hamilton, ON, CA

7 Health Policy and Management, DeGroote School of Business, McMaster University, Hamilton, ON, CA

8 Institute of Health Policy, Management and Evaluation, University of Toronto , Toronto, ON, CA

9 Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, CA

*these authors contributed equally

Corresponding Author:

  • Sankavi Muralitharan, MPharm, MSc
  • Centre for Data Science and Digital Health
  • Hamilton Health Sciences
  • 293 Wellington St. N
  • Hamilton, ON
  • CA
  • Phone: 1 2897882965
  • Email: sankavi_22@hotmail.com