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Viewpoint (42) Machine Learning (1895) Decision Support for Health Professionals (1435)
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
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JMIR Formative Res: Open-Source Clinical Machine Learning Models: Critical Appraisal of #feasibility, Advantages, a… https://t.co/0bCJDKKine

12:55 PM · Apr 11, 2022

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JMIR Formative Research JMIR Formative Research @JMIR_Formative

RT @jmirpub: JMIR Formative Res: Open-Source Clinical Machine Learning Models: Critical Appraisal of #feasibility, Advantages, and Challeng…

12:55 PM · Apr 11, 2022

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Nicholson Price Nicholson Price @WNicholsonPrice

What challenges show up in developing and sharing open-source models for medical #AI? Incentives, resources, data-… https://t.co/0up3Bqv3Y5

7:00 PM · Apr 13, 2022

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