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

Formative Evaluation of Digital Health Interventions (1482) Mobile Health (mhealth) (1924) Obstetrics, Gynecology, and Reproductive Medicine (123)

Published on in Vol 4 , No 5 (2020) :May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15094, first published .
Identifying Women at Risk for Polycystic Ovary Syndrome Using a Mobile Health App: Virtual Tool Functionality Assessment

Identifying Women at Risk for Polycystic Ovary Syndrome Using a Mobile Health App: Virtual Tool Functionality Assessment

Identifying Women at Risk for Polycystic Ovary Syndrome Using a Mobile Health App: Virtual Tool Functionality Assessment

Authors of this article:

Erika Marie Rodriguez 1, 2 Author Orcid Image ;   Daniel Thomas 3 Author Orcid Image ;   Anna Druet 3 Author Orcid Image ;   Marija Vlajic-Wheeler 3 Author Orcid Image ;   Kevin James Lane 4 Author Orcid Image ;   Shruthi Mahalingaiah 1, 2, 5 Author Orcid Image
Article Authors Cited by (2) Tweetations (8) Metrics

Journals

  1. Zheng C, Yu Y, Bai X. Polycystic ovary syndrome and related inflammation in radiomics; relationship with patient outcome. Seminars in Cell & Developmental Biology 2023 View