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

Viewpoints and Perspectives (514) Artificial Intelligence (1371) Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185) Advanced Data Analytics in eHealth (133) Ethics, Privacy, and Legal Issues (479) E-Health Policy and Health Systems Innovation (230)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50295, first published .
Resilient Artificial Intelligence in Health: Synthesis and Research Agenda Toward Next-Generation Trustworthy Clinical Decision Support

Resilient Artificial Intelligence in Health: Synthesis and Research Agenda Toward Next-Generation Trustworthy Clinical Decision Support

Resilient Artificial Intelligence in Health: Synthesis and Research Agenda Toward Next-Generation Trustworthy Clinical Decision Support

Authors of this article:

Carlos Sáez1 Author Orcid Image ;   Pablo Ferri1 Author Orcid Image ;   Juan M García-Gómez1 Author Orcid Image
Article Authors Cited by (2) Tweetations (9) Metrics

Journals

  1. Singh A, Sharma K, Bajpai M, Sarasa-Cabezuelo A. Patient centric trustworthy AI in medical analysis and disease prediction: A Comprehensive survey and taxonomy. Applied Soft Computing 2024;167:112374 View
  2. Hwang S, Lee H, Lee J, Lee M, Koyanagi A, Smith L, Rhee S, Yon D, Lee J. Machine Learning–Based Prediction for Incident Hypertension Based on Regular Health Checkup Data: Derivation and Validation in 2 Independent Nationwide Cohorts in South Korea and Japan. Journal of Medical Internet Research 2024;26:e52794 View