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

Non-randomized Protocols and Methods (ehealth) (568)

Published on in Vol 7, No 9 (2018): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9466, first published .
Validating a Machine Learning Algorithm to Predict 30-Day Re-Admissions in Patients With Heart Failure: Protocol for a Prospective Cohort Study

Validating a Machine Learning Algorithm to Predict 30-Day Re-Admissions in Patients With Heart Failure: Protocol for a Prospective Cohort Study

Validating a Machine Learning Algorithm to Predict 30-Day Re-Admissions in Patients With Heart Failure: Protocol for a Prospective Cohort Study

Authors of this article:

Sujay Kakarmath1, 2, 3 Author Orcid Image ;   Sara Golas1 Author Orcid Image ;   Jennifer Felsted1, 3 Author Orcid Image ;   Joseph Kvedar2, 3, 4 Author Orcid Image ;   Kamal Jethwani2, 3, 4 Author Orcid Image ;   Stephen Agboola1, 2, 3 Author Orcid Image
Article Authors Cited by (9) Tweetations (6) Metrics

Sujay Kakarmath   1, 2, 3 , MBBS, MSc ;   Sara Golas   1 , MA ;   Jennifer Felsted   1, 3 , PhD ;   Joseph Kvedar   2, 3, 4 , MD ;   Kamal Jethwani   2, 3, 4 , MD, MPH ;   Stephen Agboola   1, 2, 3 , MD, MPH

1 Data Science and Analytics Unit, Partners Connected Health, Partners HealthCare, Boston, MA, United States

2 Department of Dermatology, Massachusetts General Hospital, Boston, MA, United States

3 Department of Dermatology, Harvard Medical School, Boston, MA, United States

4 Partners Connected Health, Partners HealthCare, Boston, MA, United States

Corresponding Author:

  • Sujay Kakarmath, MBBS, MSc
  • Data Science and Analytics Unit
  • Partners Connected Health
  • Partners HealthCare
  • 25 New Chardon Street, Suite 300
  • Boston, MA, 02114
  • United States
  • Phone: 1 6177240041
  • Fax: 1 617-228-4619
  • Email: skakarmath@mgh.harvard.edu