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

Applications of AI (126) Artificial Intelligence (1515)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45032, first published .
An Assessment of How Clinicians and Staff Members Use a Diabetes Artificial Intelligence Prediction Tool: Mixed Methods Study

An Assessment of How Clinicians and Staff Members Use a Diabetes Artificial Intelligence Prediction Tool: Mixed Methods Study

An Assessment of How Clinicians and Staff Members Use a Diabetes Artificial Intelligence Prediction Tool: Mixed Methods Study

Authors of this article:

Winston R Liaw1 Author Orcid Image ;   Yessenia Ramos Silva2 Author Orcid Image ;   Erica G Soltero3 Author Orcid Image ;   Alex Krist4 Author Orcid Image ;   Angela L Stotts5 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

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  2. Chen H, Alfred M, Brown A, Atinga A, Cohen E. Intersection of Performance, Interpretability, and Fairness in Neural Prototype Tree for Chest X-Ray Pathology Detection: Algorithm Development and Validation Study. JMIR Formative Research 2024;8:e59045 View
  3. Tun H, Rahman H, Naing L, Malik O. Trust in AI-Based Clinical Decision Support Systems Among Healthcare Workers: A Systematic Review (Preprint). Journal of Medical Internet Research 2024 View