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

Artificial Intelligence (1371) Machine Learning (1465) Health Services in Resource-Poor Settings and LMICs (414) Diabetes Health Services and System Innovations (117) Diabetes Prevention (83) Hypertension Prevention and Treatment (224)

Published on in Vol 23, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20123, first published .
Risk Stratification for Early Detection of Diabetes and Hypertension in Resource-Limited Settings: Machine Learning Analysis

Risk Stratification for Early Detection of Diabetes and Hypertension in Resource-Limited Settings: Machine Learning Analysis

Risk Stratification for Early Detection of Diabetes and Hypertension in Resource-Limited Settings: Machine Learning Analysis

Authors of this article:

Justin J Boutilier1 Author Orcid Image ;   Timothy C Y Chan2 Author Orcid Image ;   Manish Ranjan3 Author Orcid Image ;   Sarang Deo4 Author Orcid Image
Article Authors Cited by (22) Tweetations (7) Metrics

Justin J Boutilier   1 , PhD ;   Timothy C Y Chan   2 , PhD ;   Manish Ranjan   3 , MBA ;   Sarang Deo   4 , PhD

1 Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, United States

2 Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada

3 NanoHealth, NanoCare Health Services, Hyderabad, India

4 Max Institute of Healthcare Management, Indian School of Business, Hyderabad, India

Corresponding Author:

  • Justin J Boutilier, PhD
  • Department of Industrial and Systems Engineering
  • University of Wisconsin-Madison
  • 1513 University Avenue
  • Madison, WI, 53706
  • United States
  • Phone: 1 6082630350
  • Email: jboutilier@wisc.edu