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

Mobile Health (mhealth) (3137) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1557)

Published on in Vol 20, No 11 (2018): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12001, first published .
Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods

Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods

Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods

Authors of this article:

Quazi Abidur Rahman1 Author Orcid Image ;   Tahir Janmohamed2 Author Orcid Image ;   Meysam Pirbaglou3 Author Orcid Image ;   Hance Clarke4 Author Orcid Image ;   Paul Ritvo3, 5 Author Orcid Image ;   Jane M Heffernan1 Author Orcid Image ;   Joel Katz3, 4, 5 Author Orcid Image
Article Authors Cited by (31) Tweetations (6) Metrics

Quazi Abidur Rahman   1 , PhD ;   Tahir Janmohamed   2 , PEng, MBA ;   Meysam Pirbaglou   3 , MSc ;   Hance Clarke   4 , MD, PhD, FRCPC ;   Paul Ritvo   3, 5 , PhD ;   Jane M Heffernan   1 , PhD ;   Joel Katz   3, 4, 5 , PhD

1 Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada

2 ManagingLife, Inc, Toronto, ON, Canada

3 School of Kinesiology & Health Science, York University, Toronto, ON, Canada

4 Department of Anesthesia and Pain Management, Toronto General Hospital, Toronto, ON, Canada

5 Department of Psychology, York University, Toronto, ON, Canada

Corresponding Author: