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Viewpoint (40) Machine Learning (1688) Decision Support for Health Professionals (1324)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33970, first published .
Open-Source Clinical Machine Learning Models: Critical Appraisal of Feasibility, Advantages, and Challenges

Open-Source Clinical Machine Learning Models: Critical Appraisal of Feasibility, Advantages, and Challenges

Open-Source Clinical Machine Learning Models: Critical Appraisal of Feasibility, Advantages, and Challenges

Authors of this article:

Keerthi B Harish1 Author Orcid Image ;   W Nicholson Price2, 3 Author Orcid Image ;   Yindalon Aphinyanaphongs1 Author Orcid Image
Article Authors Cited by (13) Tweetations (3) Metrics

Keerthi B Harish   1 , BA ;   W Nicholson Price   2, 3 , JD ;   Yindalon Aphinyanaphongs   1 , MD, PhD

1 Grossman School of Medicine, New York University, New York, NY, United States

2 Law School, University of Michigan, Ann Arbor, MI, United States

3 Centre for Advanced Studies In Biomedical Innovation Law, University of Copenhagen, Copenhagen, Denmark

Corresponding Author:

  • Yindalon Aphinyanaphongs, MD, PhD
  • Grossman School of Medicine
  • New York University
  • 227 East 30th St, 6th Floor
  • New York, NY, 10016
  • United States
  • Phone: 1 212-263-9041
  • Email: yin.a@nyulangone.org