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

Formative Evaluation of Digital Health Interventions (2491) Machine Learning (1501) Clinical Informatics (1050)

Published on in Vol 6, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29967, first published .
Machine-Aided Self-diagnostic Prediction Models for Polycystic Ovary Syndrome: Observational Study

Machine-Aided Self-diagnostic Prediction Models for Polycystic Ovary Syndrome: Observational Study

Machine-Aided Self-diagnostic Prediction Models for Polycystic Ovary Syndrome: Observational Study

Authors of this article:

Angela Zigarelli1 Author Orcid Image ;   Ziyang Jia1 Author Orcid Image ;   Hyunsun Lee1 Author Orcid Image
Article Authors Cited by (20) Tweetations (2) Metrics

Angela Zigarelli   1 , MSc ;   Ziyang Jia   1 , MSc ;   Hyunsun Lee   1 , PhD

1 Department of Mathematics and Statistics, University of Massachusetts Amherst, Newton, MA, United States

Corresponding Author:

  • Hyunsun Lee, PhD
  • Department of Mathematics and Statistics
  • University of Massachusetts Amherst
  • 100 Carlson Ave
  • Newton, MA, 02459
  • United States
  • Phone: 1 6172431886
  • Email: hyunsunlee@umass.edu