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

Coronary Heart Disease (97) Clinical Information and Decision Making (1665) Machine Learning (1748) Cardiac Risk and Cardiac Risk Calculators (70)

Published on in Vol 4, No 1 (2020): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16975, first published .
Minimal Patient Clinical Variables to Accurately Predict Stress Echocardiography Outcome: Validation Study Using Machine Learning Techniques

Minimal Patient Clinical Variables to Accurately Predict Stress Echocardiography Outcome: Validation Study Using Machine Learning Techniques

Minimal Patient Clinical Variables to Accurately Predict Stress Echocardiography Outcome: Validation Study Using Machine Learning Techniques

Authors of this article:

Mohamed Bennasar1 Author Orcid Image ;   Duncan Banks2 Author Orcid Image ;   Blaine A Price1 Author Orcid Image ;   Attila Kardos3 Author Orcid Image
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New in JMIR Cardio: Minimal Patient Clinical Variables to Accurately Predict Stress Echo#cardiography Outcome: Vali… https://t.co/u6w6JK2HKT

2:35 PM · May 29, 2020

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Dmitri Katz Dmitri Katz @dmitri_katz

RT @bp5: My latest #JMIRCardio paper is out: https://t.co/0fvus16BdA https://t.co/Hh0unD03GV

6:43 AM · Jun 02, 2020

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OUComputing OUComputing @OUComputing

By our @OUComputing colleague, @bp5 ???????? #digitalhealth https://t.co/kNQZDI99dn

4:47 AM · Jun 16, 2020

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