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

Tools, Programs and Algorithms (266) Digital Health Reviews (1289) Machine Learning (1465)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38266, first published .
Scalable Causal Structure Learning: Scoping Review of Traditional and Deep Learning Algorithms and New Opportunities in Biomedicine

Scalable Causal Structure Learning: Scoping Review of Traditional and Deep Learning Algorithms and New Opportunities in Biomedicine

Scalable Causal Structure Learning: Scoping Review of Traditional and Deep Learning Algorithms and New Opportunities in Biomedicine

Authors of this article:

Pulakesh Upadhyaya1, 2 Author Orcid Image ;   Kai Zhang1 Author Orcid Image ;   Can Li1 Author Orcid Image ;   Xiaoqian Jiang1 Author Orcid Image ;   Yejin Kim1 Author Orcid Image
Article Authors Cited by (3) Tweetations (7) Metrics

Pulakesh Upadhyaya   1, 2 , PhD ;   Kai Zhang   1 , PhD ;   Can Li   1 , MSPH ;   Xiaoqian Jiang   1 , PhD ;   Yejin Kim   1 , PhD

1 School of Biomedical Informatics, University of Texas Health Science Center at Houston, HOUSTON, TX, United States

2 Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, United States

Corresponding Author:

  • Pulakesh Upadhyaya, PhD
  • Department of Biomedical Informatics
  • Emory University School of Medicine
  • 101 Woodruff Circle
  • Suite 4127
  • Atlanta, GA, 30322
  • United States
  • Phone: 1 9794225161
  • Email: pulakeshupadhyaya@gmail.com