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

Viewpoints and Perspectives (514) Clinical Information and Decision Making (1407) Viewpoints on and Experiences with Digital Technologies in Health (79) Artificial Intelligence (1371) Machine Learning (1465) Pediatrics (201) Involvement of Pediatric Populations in Health and Health Services Research (16) Artificial Intelligence (86)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49022, first published .
Promises, Pitfalls, and Clinical Applications of Artificial Intelligence in Pediatrics

Promises, Pitfalls, and Clinical Applications of Artificial Intelligence in Pediatrics

Promises, Pitfalls, and Clinical Applications of Artificial Intelligence in Pediatrics

Authors of this article:

Hansa Bhargava1, 2, 3 Author Orcid Image ;   Carmela Salomon4 Author Orcid Image ;   Srinivasan Suresh5, 6 Author Orcid Image ;   Anthony Chang7 Author Orcid Image ;   Rachel Kilian8 Author Orcid Image ;   Diana van Stijn9 Author Orcid Image ;   Albert Oriol10 Author Orcid Image ;   Daniel Low11 Author Orcid Image ;   Ashley Knebel4 Author Orcid Image ;   Sharief Taraman4, 12, 13 Author Orcid Image
Article Authors Cited by (1) Tweetations (5) Metrics

Journals

  1. Chou F, Rowen N, Javier J, Lakshmanan A. Predicting childhood outcomes through standardizing disease definitions and promoting multicenter enrollment. Pediatric Research 2024;96(5):1103 View