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

Journals

  1. Basile P, Falagario A, Carella M, Dicorato M, Monitillo F, Santoro D, Naccarati M, Pontone G, Ciccone M, Santobuono V, Guaricci A. Eligibility of Outpatients with Chronic Heart Failure for Vericiguat and Omecamtiv Mecarbil: From Clinical Trials to the Real-World Practice. Journal of Clinical Medicine 2025;14(6):1951 View
  2. Kumar N, Agarwal R, Sharma L, Vashisth R. Machine Learning-Based Ensemble Predictive Model for Cardiovascular Disease Prevention. International Journal of Angiology 2025 View
  3. Abdelwanis M, Simsekler M, Gabor A, Sleptchenko A, Omar M. Artificial intelligence adoption challenges from healthcare providers’ perspectives: A comprehensive review and future directions. Safety Science 2026;193:107028 View
  4. Bhandari A, Riaz I, Hariram S, Izaguirre Vallejos C, Gupta S, Sharma K, Palaparthi E, Kyaw P, Reddy Seelam C, Tiwary S, Narayanan P, Imtiaz M, Ali R. AI Tools for Heart Failure Management: A Comprehensive Review of Potential, Pitfalls, and Predictive Analytics. Cureus 2025 View
  5. Cao Y, Deng L, Liu X, Feng Z, Gao Y. Ethical challenges in the algorithmic era: a systematic rapid review of risk insights and governance pathways for nursing predictive analytics and early warning systems. BMC Medical Ethics 2025;26(1) View