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

Ontologies, Classifications, and Coding (324) Chronic Conditions (434) Gastroenterology and Hepatology (127) Decision Support for Health Professionals (1539) Electronic Health Records (1319) Machine Learning (2076) Clinical Informatics (1325) Clinical Information and Decision Making (1915) Theoretical Frameworks and Concepts (338)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63581, first published .
Predicting Unplanned Readmission Risk in Patients With Cirrhosis: Complication-Aware Dynamic Classifier Selection Approach

Predicting Unplanned Readmission Risk in Patients With Cirrhosis: Complication-Aware Dynamic Classifier Selection Approach

Predicting Unplanned Readmission Risk in Patients With Cirrhosis: Complication-Aware Dynamic Classifier Selection Approach

Authors of this article:

Zixin Shi1 Author Orcid Image ;   Linjun Huang1 Author Orcid Image ;   Xiaomei Xu2 Author Orcid Image ;   Kexue Pu1 Author Orcid Image ;   Qingpeng Zhang3, 4 Author Orcid Image ;   Haolin Wang1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Eskandar K. Artificial intelligence in hepatology: A comprehensive scoping review of clinical applications, challenges, and future directions. iLIVER 2025;4(4):100205 View