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

Machine Learning (1364) Artificial Intelligence (1174) Public (e)Health, Digital Epidemiology and Public Health Informatics (632) Cardiac Risk and Cardiac Risk Calculators (32) Clinical Information and Decision Making (1303) Secondary Use of Clinical Data for Research and Surveillance (312) Decision Support for Health Professionals (1112)

Published on in Vol 9, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25000, first published .
Mortality Prediction of Patients With Cardiovascular Disease Using Medical Claims Data Under Artificial Intelligence Architectures: Validation Study

Mortality Prediction of Patients With Cardiovascular Disease Using Medical Claims Data Under Artificial Intelligence Architectures: Validation Study

Mortality Prediction of Patients With Cardiovascular Disease Using Medical Claims Data Under Artificial Intelligence Architectures: Validation Study

Authors of this article:

Linh Tran1 Author Orcid Image ;   Lianhua Chi2 Author Orcid Image ;   Alessio Bonti1 Author Orcid Image ;   Mohamed Abdelrazek1 Author Orcid Image ;   Yi-Ping Phoebe Chen2 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Gopukumar D, Ghoshal A, Zhao H. Predicting Readmission Charges Billed by Hospitals: Machine Learning Approach. JMIR Medical Informatics 2022;10(8):e37578 View
  2. Petersson L, Vincent K, Svedberg P, Nygren J, Larsson I. Ethical considerations in implementing AI for mortality prediction in the emergency department: Linking theory and practice. DIGITAL HEALTH 2023;9 View