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

Involvement of Elderly Populations in Health and Health Services Research (67) Cardiology (245) Advanced Data Analytics in eHealth (250) Cardiac Risk and Cardiac Risk Calculators (125)

Published on in Vol 6 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51844, first published .
Orange defibrillator AED box mounted on a brick wall, with a Samaritan PAD device visible inside.

Joint Modeling of Social Determinants and Clinical Factors to Define Subphenotypes in Out-of-Hospital Cardiac Arrest Survival: Cluster Analysis

Joint Modeling of Social Determinants and Clinical Factors to Define Subphenotypes in Out-of-Hospital Cardiac Arrest Survival: Cluster Analysis

Authors of this article:

Ethan E Abbott1, 2, 3, 4 Author Orcid Image ;   Wonsuk Oh3, 5, 6 Author Orcid Image ;   Yang Dai6 Author Orcid Image ;   Cole Feuer6 Author Orcid Image ;   Lili Chan3, 6, 7 Author Orcid Image ;   Brendan G Carr1, 4 Author Orcid Image ;   Girish N Nadkarni2, 3, 5, 6, 7 Author Orcid Image
Article Authors Cited by (2) Tweetations (7) Metrics

Journals

  1. Oh W, Veshtaj M, Sakhuja A. Enriching patient populations in ICU trials: reducing heterogeneity through machine learning. Current Opinion in Critical Care 2025;31(4):410 View
  2. Miles J, Brady M, Smith L, Cotterill C, Levey C. Use of artificial intelligence in the out-of-hospital care settings: a scoping review. BMJ Digital Health & AI 2026;2(1):e000035 View