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

Ontologies, Classifications, and Coding (307) Chronic Conditions (396) Gastroenterology and Hepatology (102) Decision Support for Health Professionals (1459) Electronic Health Records (1265) Machine Learning (1948) Clinical Informatics (1250) Clinical Information and Decision Making (1798) Theoretical Frameworks and Concepts (323)

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 Tweetations Metrics

Zixin Shi   1 , MS ;   Linjun Huang   1 , BE ;   Xiaomei Xu   2 , MD ;   Kexue Pu   1 , PhD ;   Qingpeng Zhang   3, 4 , PhD ;   Haolin Wang   1 , PhD

1 College of Medical Informatics, Chongqing Medical University, Chongqing, China

2 Department of Infectious Diseases, Chengdu Fifth People's Hospital, Chengdu, China

3 Musketeers Foundation Institute of Data Science, University of Hong Kong, Hong Kong, China (Hong Kong)

4 Department of Pharmacology and Pharmacy, University of Hong Kong, Hong Kong, China (Hong Kong)

Corresponding Author:

  • Haolin Wang, PhD
  • College of Medical Informatics
  • Chongqing Medical University
  • 1 Yixueyuan Road, Yuzhong District
  • Chongqing 400016
  • China
  • Phone: 86 13500303273
  • Email: haolinwang@cqmu.edu.cn