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

Machine Learning (1401) Artificial Intelligence (1216) Adoption and Change Management of eHealth Systems (677) Clinical Information and Decision Making (1340)

Published on in Vol 10, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37578, first published .
Predicting Readmission Charges Billed by Hospitals: Machine Learning Approach

Predicting Readmission Charges Billed by Hospitals: Machine Learning Approach

Predicting Readmission Charges Billed by Hospitals: Machine Learning Approach

Authors of this article:

Deepika Gopukumar1 Author Orcid Image ;   Abhijeet Ghoshal2 Author Orcid Image ;   Huimin Zhao3 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

Journals

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  2. Lashen H, St John T, Almallah Y, Sasidhar M, Shamout F. Machine Learning Models Versus the National Early Warning Score System for Predicting Deterioration: Retrospective Cohort Study in the United Arab Emirates. JMIR AI 2023;2:e45257 View
  3. Wang S, Barrette L, Ng J, Sangal N, Cannady S, Brody R, Bur A, Brant J. Predicting reoperation and readmission for head and neck free flap patients using machine learning. Head & Neck 2024;46(8):1999 View
  4. Aggarwal S, Singh R, Rathore A, Kapoor K, Patel M. A Novel Data-driven Machine Learning Techniques to Predict Compressive Strength of Fly Ash and Recycled Coarse Aggregates Based Self-Compacting Concrete. Materials Today Communications 2024:109294 View

Books/Policy Documents

  1. Ragunathan B, Bachmann N, Dornberger R, Hanne T. Proceedings of International Conference on Computational Intelligence. View