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

Decision Support for Health Professionals (1210) Clinical Informatics (1050) Clinical Information and Decision Making (1434) Secondary Use of Clinical Data for Research and Surveillance (375) Machine Learning (1501)

Published on in Vol 9, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16306, first published .
Early Prediction of Unplanned 30-Day Hospital Readmission: Model Development and Retrospective Data Analysis

Early Prediction of Unplanned 30-Day Hospital Readmission: Model Development and Retrospective Data Analysis

Early Prediction of Unplanned 30-Day Hospital Readmission: Model Development and Retrospective Data Analysis

Authors of this article:

Peng Zhao1 Author Orcid Image ;   Illhoi Yoo1, 2 Author Orcid Image ;   Syed H Naqvi3 Author Orcid Image
Article Authors Cited by (19) Tweetations (1) Metrics

Journals

  1. Shafiekhani S, Namdar P, Rafiei S. A COVID-19 forecasting system for hospital needs using ANFIS and LSTM models: A graphical user interface unit. DIGITAL HEALTH 2022;8:205520762210850 View
  2. Michailidis P, Dimitriadou A, Papadimitriou T, Gogas P. Forecasting Hospital Readmissions with Machine Learning. Healthcare 2022;10(6):981 View
  3. Davis S, Zhang J, Lee I, Rezaei M, Greiner R, McAlister F, Padwal R. Effective hospital readmission prediction models using machine-learned features. BMC Health Services Research 2022;22(1) View
  4. Gopukumar D, Ghoshal A, Zhao H. Predicting Readmission Charges Billed by Hospitals: Machine Learning Approach. JMIR Medical Informatics 2022;10(8):e37578 View
  5. Shanbehzadeh M, Yazdani A, Shafiee M, Kazemi-Arpanahi H. Predictive modeling for COVID-19 readmission risk using machine learning algorithms. BMC Medical Informatics and Decision Making 2022;22(1) View
  6. Afrash M, Kazemi-Arpanahi H, Shanbehzadeh M, Nopour R, Mirbagheri E. Predicting hospital readmission risk in patients with COVID-19: A machine learning approach. Informatics in Medicine Unlocked 2022;30:100908 View
  7. Yang P, Qiu H, Wang L, Zhou L. Early prediction of high-cost inpatients with ischemic heart disease using network analytics and machine learning. Expert Systems with Applications 2022;210:118541 View
  8. Tang S, Tariq A, Dunnmon J, Sharma U, Elugunti P, Rubin D, Patel B, Banerjee I. Predicting 30-day all-cause hospital readmission using multimodal spatiotemporal graph neural networks. IEEE Journal of Biomedical and Health Informatics 2023:1 View
  9. Ru B, Tan X, Liu Y, Kannapur K, Ramanan D, Kessler G, Lautsch D, Fonarow G. Comparison of Machine Learning Algorithms for Predicting Hospital Readmissions and Worsening Heart Failure Events in Patients With Heart Failure With Reduced Ejection Fraction: Modeling Study. JMIR Formative Research 2023;7:e41775 View
  10. Han S, Sohn T, Ng B, Park C. Predicting unplanned readmission due to cardiovascular disease in hospitalized patients with cancer: a machine learning approach. Scientific Reports 2023;13(1) View
  11. Song X, Tong Y, Luo Y, Chang H, Gao G, Dong Z, Wu X, Tong R. Predicting 7-day unplanned readmission in elderly patients with coronary heart disease using machine learning. Frontiers in Cardiovascular Medicine 2023;10 View
  12. Bedoya J, Castro J. Explainability analysis in predictive models based on machine learning techniques on the risk of hospital readmissions. Health and Technology 2024;14(1):93 View
  13. Mercurio G, Gottardelli B, Lenkowicz J, Patarnello S, Bellavia S, Scala I, Rizzo P, de Belvis A, Del Signore A, Maviglia R, Bocci M, Olivi A, Franceschi F, Urbani A, Calabresi P, Valentini V, Antonelli M, Frisullo G. A novel risk score predicting 30‐day hospital re‐admission of patients with acute stroke by machine learning model. European Journal of Neurology 2024;31(3) View
  14. Askar M, Småbrekke L, Holsbø E, Bongo L, Svendsen K. “Using network analysis modularity to group health code systems and decrease dimensionality in machine learning models”. Exploratory Research in Clinical and Social Pharmacy 2024;14:100463 View
  15. Wu D, Shi Y, Wang C, Li C, Lu Y, Wang C, Zhu W, Sun T, Han J, Zheng Y, Zhang L. Investigating the impact of extreme weather events and related indicators on cardiometabolic multimorbidity. Archives of Public Health 2024;82(1) View
  16. Tao Y, Zhu R, Wu D. Harnessing the Power of Complementarity Between Smart Tracking Technology and Associated Health Information Technologies: Longitudinal Study. JMIR Formative Research 2024;8:e51198 View
  17. Davis S, Greiner R. Survival models and longitudinal medical events for hospital readmission forecasting. BMC Health Services Research 2024;24(1) View