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

Formative Evaluation of Digital Health Interventions (2491) Artificial Intelligence (1421) Clinical Informatics (1050) Clinical Information and Decision Making (1434) Decision Support for Health Professionals (1210) E-Health / Health Services Research and New Models of Care (542) Machine Learning (1501)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43963, first published .
Development and Integration of Machine Learning Algorithm to Identify Peripheral Arterial Disease: Multistakeholder Qualitative Study

Development and Integration of Machine Learning Algorithm to Identify Peripheral Arterial Disease: Multistakeholder Qualitative Study

Development and Integration of Machine Learning Algorithm to Identify Peripheral Arterial Disease: Multistakeholder Qualitative Study

Authors of this article:

Sabrina M Wang1 Author Orcid Image ;   H D Jeffry Hogg2, 3 Author Orcid Image ;   Devdutta Sangvai4 Author Orcid Image ;   Manesh R Patel5 Author Orcid Image ;   E Hope Weissler6 Author Orcid Image ;   Katherine C Kellogg7 Author Orcid Image ;   William Ratliff8 Author Orcid Image ;   Suresh Balu8 Author Orcid Image ;   Mark Sendak8 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Rajagopal A, Ayanian S, Ryu A, Qian R, Legler S, Peeler E, Issa M, Coons T, Kawamoto K. Machine Learning Operations in Health Care: A Scoping Review. Mayo Clinic Proceedings: Digital Health 2024;2(3):421 View
  2. Ayorinde A, Mensah D, Walsh J, Ghosh I, Ibrahim S, Hogg J, Peek N, Griffiths F. Health Care Professionals’ Experience of Using AI: Systematic Review With Narrative Synthesis. Journal of Medical Internet Research 2024;26:e55766 View