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

Machine Learning (2066) Clinical Informatics (1316) Cardiac Risk and Cardiac Risk Calculators (102) Electronic Health Records (1314) Clinical Information and Decision Making (1908) Decision Support for Health Professionals (1531)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73020, first published .
Predicting 30-Days Hospital Readmission for Patients with Heart Failure Using Electronic Health Record Embeddings: Comparative Evaluation

Predicting 30-Days Hospital Readmission for Patients with Heart Failure Using Electronic Health Record Embeddings: Comparative Evaluation

Predicting 30-Days Hospital Readmission for Patients with Heart Failure Using Electronic Health Record Embeddings: Comparative Evaluation

Authors of this article:

Prabin Shakya1 Author Orcid Image ;   Ayush Khaneja1 Author Orcid Image ;   Kavishwar B Wagholikar1, 2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Prabin Shakya   1 , MSc ;   Ayush Khaneja   1 , MSc ;   Kavishwar B Wagholikar   1, 2 , PhD, MD

1 Laboratory of Computer Science, Massachusetts General Hospital, Boston, MA, United States

2 Harvard Medical School, Boston, MA, United States

Corresponding Author:

  • Prabin Shakya, MSc
  • Laboratory of Computer Science
  • Massachusetts General Hospital
  • 399 Revolution Drive, 7th Floor
  • Boston, MA 02145
  • United States
  • Phone: 1 8595360114
  • Email: prabinrs@gmail.com