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

Research Methodology - AI (14) Innovative Methods in Public Health and Surveillance (336) Machine Learning (1501) Diabetes (194) Diabetes Health Services and System Innovations (119) Diabetes Surveillance and Epidemiology (27) Diabetes-specific EHR Improvements (33) Tools, Programs and Algorithms (275) Clinical Informatics (1050)

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58463, first published .
Machine Learning–Based Prediction for High Health Care Utilizers by Using a Multi-Institutional Diabetes Registry: Model Training and Evaluation

Machine Learning–Based Prediction for High Health Care Utilizers by Using a Multi-Institutional Diabetes Registry: Model Training and Evaluation

Machine Learning–Based Prediction for High Health Care Utilizers by Using a Multi-Institutional Diabetes Registry: Model Training and Evaluation

Authors of this article:

Joshua Kuan Tan1 Author Orcid Image ;   Le Quan2 Author Orcid Image ;   Nur Nasyitah Mohamed Salim1 Author Orcid Image ;   Jen Hong Tan2 Author Orcid Image ;   Su-Yen Goh3 Author Orcid Image ;   Julian Thumboo1 Author Orcid Image ;   Yong Mong Bee3 Author Orcid Image
Article Authors Cited by Tweetations (2) Metrics

There are no citations yet available for this article according to Crossref .