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Machine Learning (2219) Clinical Information and Decision Making (2055) Decision Support for Health Professionals (1627) Electronic Health Records (1371) Clinical Informatics (1428) Artificial Intelligence (2325) New Methods (1176)

Published on in Vol 9, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32662, first published .
Machine Learning–Based Hospital Discharge Prediction for Patients With Cardiovascular Diseases: Development and Usability Study

Machine Learning–Based Hospital Discharge Prediction for Patients With Cardiovascular Diseases: Development and Usability Study

Machine Learning–Based Hospital Discharge Prediction for Patients With Cardiovascular Diseases: Development and Usability Study

Authors of this article:

Imjin Ahn1 Author Orcid Image ;   Hansle Gwon1 Author Orcid Image ;   Heejun Kang2 Author Orcid Image ;   Yunha Kim1 Author Orcid Image ;   Hyeram Seo1 Author Orcid Image ;   Heejung Choi1 Author Orcid Image ;   Ha Na Cho2 Author Orcid Image ;   Minkyoung Kim2 Author Orcid Image ;   Tae Joon Jun3 Author Orcid Image ;   Young-Hak Kim2 Author Orcid Image
Article Authors Cited by (13) Tweetations (5) Metrics

Journals

  1. Subramani S, Varshney N, Anand M, Soudagar M, Al-keridis L, Upadhyay T, Alshammari N, Saeed M, Subramanian K, Anbarasu K, Rohini K. Cardiovascular diseases prediction by machine learning incorporation with deep learning. Frontiers in Medicine 2023;10 View
  2. Zalikha L, Court T, Nham F, El-Othmani M, Shah R. Improved performance of machine learning models in predicting length of stay, discharge disposition, and inpatient mortality after total knee arthroplasty using patient-specific variables. Arthroplasty 2023;5(1) View
  3. Pahlevani M, Taghavi M, Vanberkel P. A systematic literature review of predicting patient discharges using statistical methods and machine learning. Health Care Management Science 2024;27(3):458 View
  4. Saarela M, Podgorelec V. Recent Applications of Explainable AI (XAI): A Systematic Literature Review. Applied Sciences 2024;14(19):8884 View
  5. Wei J, Zhou J, Zhang Z, Yuan K, Gu Q, Luk A, Brent A, Clifton D, Walker A, Eyre D. Predicting individual patient and hospital-level discharge using machine learning. Communications Medicine 2024;4(1) View
  6. Pahlevani M, Rajabi E, Taghavi M, VanBerkel P. Developing a decision support tool to predict delayed discharge from hospitals using machine learning. BMC Health Services Research 2025;25(1) View
  7. Ramakrishnaiah Y, Macesic N, Webb G, Peleg A, Tyagi S. EHR-ML: A data-driven framework for designing machine learning applications with electronic health records. International Journal of Medical Informatics 2025;196:105816 View
  8. Mandal A, Dehuri S, Sarma P. Analysis of machine learning approaches for predictive modeling in heart disease detection systems. Biomedical Signal Processing and Control 2025;106:107723 View
  9. Zhang Z, Su M, Jiang P, Wang X, Kong L, Tong X, Wu G. Interpretable machine learning model to predict 90-day radiographically confirmed pneumonia after chemotherapy initiation in non-Hodgkin lymphoma: development and internal validation of a single-center cohort. Frontiers in Medicine 2025;12 View
  10. Alghamdi S, Mehmood R, Alqurashi F, Alzahrani A. Paving the Roadmap for XAI and IML in Healthcare: Data-Driven Discoveries and the FIXAIH Framework. IEEE Access 2025;13:174393 View

Books/Policy Documents

  1. Goyal R, Anand D, Mukhija L, Juneja S, Atwal S. Micro-electronics and Telecommunication Engineering. View

Conference Proceedings

  1. Jia B, Zhang J, Jia X. 2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). Predict Turnaround Time of Hospital Discharge View
  2. Parate J, Umate L. 2025 3rd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIHEI). Reducing Delayed Hospital Discharges Through AI-Driven Documentation and Machine Learning–Based Predictive Models: Impacts on Patient Flow, Length of Stay, and Operational Efficiency View