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

Urology (15) Machine Learning (1378) Clinical Information and Decision Making (1320) Electronic Health Records (965) Secondary Use of Clinical Data for Research and Surveillance (319) Decision Support for Health Professionals (1132)

Published on in Vol 11, No 1 (2022): Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33357, first published .
A Machine Learning Approach to Predict the Outcome of Urinary Calculi Treatment Using Shock Wave Lithotripsy: Model Development and Validation Study

A Machine Learning Approach to Predict the Outcome of Urinary Calculi Treatment Using Shock Wave Lithotripsy: Model Development and Validation Study

A Machine Learning Approach to Predict the Outcome of Urinary Calculi Treatment Using Shock Wave Lithotripsy: Model Development and Validation Study

Authors of this article:

Reihaneh Moghisi1 Author Orcid Image ;   Christo El Morr2 Author Orcid Image ;   Kenneth T Pace3, 4 Author Orcid Image ;   Mohammad Hajiha5 Author Orcid Image ;   Jimmy Huang1 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

Reihaneh Moghisi   1 * , MSci ;   Christo El Morr   2 * , PhD ;   Kenneth T Pace   3, 4 , MD, PhD ;   Mohammad Hajiha   5 , MD ;   Jimmy Huang   1 , PhD

1 School of Information Technology, York University, Toronto, ON, Canada

2 School of Health Policy and Management, York University, Toronto, ON, Canada

3 Division of Urology, St Michael's Hospital, Toronto, ON, Canada

4 Department of Surgery, University of Toronto, Toronto, ON, Canada

5 Department of Urology, Loma Linda University Health, Loma Linda, CA, United States

*these authors contributed equally

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