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

E-Health / Health Services Research and New Models of Care (733) Machine Learning (2121) Artificial Intelligence (2187) Cardiology (230)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54990, first published .
Health Care Professionals and Data Scientists’ Perspectives on a Machine Learning System to Anticipate and Manage the Risk of Decompensation From Patients With Heart Failure: Qualitative Interview Study

Health Care Professionals and Data Scientists’ Perspectives on a Machine Learning System to Anticipate and Manage the Risk of Decompensation From Patients With Heart Failure: Qualitative Interview Study

Health Care Professionals and Data Scientists’ Perspectives on a Machine Learning System to Anticipate and Manage the Risk of Decompensation From Patients With Heart Failure: Qualitative Interview Study

Authors of this article:

Joana Seringa1 Author Orcid Image ;   Anna Hirata2 Author Orcid Image ;   Ana Rita Pedro1 Author Orcid Image ;   Rui Santana1 Author Orcid Image ;   Teresa Magalhães1 Author Orcid Image
Article Authors Cited by (5) Tweetations (1) Metrics

Joana Seringa   1 , MSc ;   Anna Hirata   2 , BA ;   Ana Rita Pedro   1 , PhD ;   Rui Santana   1 , PhD ;   Teresa Magalhães   1 , PhD

1 NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, NOVA University Lisbon, Lisbon, Portugal

2 NOVA National School of Public Health, NOVA University Lisbon, Lisbon, Portugal

Corresponding Author:

  • Joana Seringa, MSc
  • NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, NOVA University Lisbon
  • Avenida Padre Cruz
  • Lisbon 1600-407
  • Portugal
  • Phone: 351 910417628
  • Email: jm.seringa@ensp.unl.pt