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Published on in Vol 7, No 4 (2019): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14756, first published .
Readmission Risk Trajectories for Patients With Heart Failure Using a Dynamic Prediction Approach: Retrospective Study

Readmission Risk Trajectories for Patients With Heart Failure Using a Dynamic Prediction Approach: Retrospective Study

Readmission Risk Trajectories for Patients With Heart Failure Using a Dynamic Prediction Approach: Retrospective Study

Authors of this article:

Wei Jiang1 Author Orcid Image ;   Sauleh Siddiqui1 Author Orcid Image ;   Sean Barnes2 Author Orcid Image ;   Lili A Barouch3 Author Orcid Image ;   Frederick Korley4 Author Orcid Image ;   Diego A Martinez5 Author Orcid Image ;   Matthew Toerper5 Author Orcid Image ;   Stephanie Cabral6 Author Orcid Image ;   Eric Hamrock7, 8 Author Orcid Image ;   Scott Levin5 Author Orcid Image
Article Authors Cited by (19) Tweetations (2) Metrics

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  7. Sharma V, KULKARNI V, MCALISTER F, EURICH D, KESHWANI S, SIMPSON S, VOAKLANDER D, SAMANANI S. Predicting 30-Day Readmissions in Patients With Heart Failure Using Administrative Data: A Machine Learning Approach. Journal of Cardiac Failure 2022;28(5):710 View
  8. Kazmi S, Kambhampati C, Cleland J, Cuthbert J, Kazmi K, Pellicori P, Rigby A, Clark A. Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure. ESC Heart Failure 2022;9(5):3009 View
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  14. Sharma V, Joon T, Kulkarni V, Samanani S, Simpson S, Voaklander D, Eurich D. Predicting 30-day risk from benzodiazepine/Z-drug dispensations in older adults using administrative data: A prognostic machine learning approach. International Journal of Medical Informatics 2023;178:105177 View
  15. Soliman A, Agvall B, Etminani K, Hamed O, Lingman M. The Price of Explainability in Machine Learning Models for 100-Day Readmission Prediction in Heart Failure: Retrospective, Comparative, Machine Learning Study. Journal of Medical Internet Research 2023;25:e46934 View
  16. Sharma V, Kulkarni V, Joon T, Eurich D, Simpson S, Voaklander D, Wright B, Samanani S. Predicting falls-related admissions in older adults in Alberta, Canada: a machine-learning falls prevention tool developed using population administrative health data. BMJ Open 2023;13(8):e071321 View
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  18. Zhang W, Cheng W, Fujiwara K, Evans R, Zhu C. Predictive Modeling for Hospital Readmissions for Patients With Heart Disease: An Updated Review From 2012–2023. IEEE Journal of Biomedical and Health Informatics 2024;28(4):2259 View
  19. Fares M, Liu H, da Silva Etges A, Zhang B, Warner J, Olson J, Fedorka C, Khan A, Best M, Kirsch J, Simon J, Sanders B, Costouros J, Zhang X, Jones P, Haas D, Abboud J. Utility of Machine Learning, Natural Language Processing, and Artificial Intelligence in Predicting Hospital Readmissions After Orthopaedic Surgery. JBJS Reviews 2024;12(8) View