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

Novel Sensors and Data Acquisition Methods in Cardiology (200) Machine Learning (1501) Clinical Information and Decision Making (1434) Wearable Devices and Sensors (903) Portable and Mobile Technologies for Rehabilitation (156) Assistive Technologies (118) Clinical Informatics (1050) Machine Learning (55)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45130, first published .
Cloud-Based Machine Learning Platform to Predict Clinical Outcomes at Home for Patients With Cardiovascular Conditions Discharged From Hospital: Clinical Trial

Cloud-Based Machine Learning Platform to Predict Clinical Outcomes at Home for Patients With Cardiovascular Conditions Discharged From Hospital: Clinical Trial

Cloud-Based Machine Learning Platform to Predict Clinical Outcomes at Home for Patients With Cardiovascular Conditions Discharged From Hospital: Clinical Trial

Authors of this article:

Phillip C Yang1, 2 Author Orcid Image ;   Alokkumar Jha1, 2 Author Orcid Image ;   William Xu2, 3 Author Orcid Image ;   Zitao Song2, 4 Author Orcid Image ;   Patrick Jamp2, 5 Author Orcid Image ;   Jeffrey J Teuteberg1 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Journals

  1. Choi J, Han E, Yoo T. Application of ChatGPT-4 to oculomics: a cost-effective osteoporosis risk assessment to enhance management as a proof-of-principles model in 3PM. EPMA Journal 2024;15(4):659 View