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

Text-messaging (SMS, WeChat etc)-Based Interventions (663) New Methods (963) Machine Learning (1501) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1428) Cardiovascular Disease Prevention (142)

Published on in Vol 8, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19200, first published .
Use of a Machine Learning Program to Correctly Triage Incoming Text Messaging Replies From a Cardiovascular Text–Based Secondary Prevention Program: Feasibility Study

Use of a Machine Learning Program to Correctly Triage Incoming Text Messaging Replies From a Cardiovascular Text–Based Secondary Prevention Program: Feasibility Study

Use of a Machine Learning Program to Correctly Triage Incoming Text Messaging Replies From a Cardiovascular Text–Based Secondary Prevention Program: Feasibility Study

Authors of this article:

Nicole Lowres1, 2 Author Orcid Image ;   Andrew Duckworth3 Author Orcid Image ;   Julie Redfern2, 4 Author Orcid Image ;   Aravinda Thiagalingam2, 4, 5 Author Orcid Image ;   Clara K Chow2, 4, 5 Author Orcid Image
Article Authors Cited by (9) Tweetations (1) Metrics

Nicole Lowres   1, 2 , BPhty, PhD ;   Andrew Duckworth   3 , BSc (Comp Sc Hons 1) ;   Julie Redfern   2, 4 , PhD, BAppSc (Physio Hons 1), BSc ;   Aravinda Thiagalingam   2, 4, 5 , MB ChB, PhD, FRACP, FCSANZ ;   Clara K Chow   2, 4, 5 , MBBS, PhD

1 Heart Research Institute, Sydney, Australia

2 Faculty of Medicine and Health, University of Sydney, Sydney, Australia

3 NA, NA, Australia

4 Westmead Applied Research Centre, University of Sydney, Sydney, Australia

5 Department of Cardiology, Westmead Hospital, Sydney, Australia

Corresponding Author: