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

Machine Learning (1962) Advanced Data Analytics in eHealth (193) Big Data (304) Nursing (125) Clinical Information and Decision Making (1805) Decision Support for Health Professionals (1466) Electronic Health Records (1268)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56671, first published .
Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study

Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study

Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study

Authors of this article:

Eui Geum Oh1, 2, 3 Author Orcid Image ;   Sunyoung Oh4 Author Orcid Image ;   Seunghyeon Cho5 Author Orcid Image ;   Mir Moon3, 6, 7 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Yuan Z, Che D, Yang Z, Yang Y, Cao D. Recognition of molecular clusters and a novel prognostic signature based on natural killer cell-related genes in skin cutaneous melanoma. World Journal of Surgical Oncology 2025;23(1) View