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

Machine Learning (2072) Clinical Informatics (1323) Evaluation and Research Methodology for mHealth (242) Artificial Intelligence (2121) Development and Evaluation of Research Methods, Instruments and Tools (743)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78309, first published .
Unsupervised Characterization of Temporal Dataset Shifts as an Early Indicator of AI Performance Variations: Evaluation Study Using the Medical Information Mart for Intensive Care-IV Dataset

Unsupervised Characterization of Temporal Dataset Shifts as an Early Indicator of AI Performance Variations: Evaluation Study Using the Medical Information Mart for Intensive Care-IV Dataset

Unsupervised Characterization of Temporal Dataset Shifts as an Early Indicator of AI Performance Variations: Evaluation Study Using the Medical Information Mart for Intensive Care-IV Dataset

Authors of this article:

David Fernández-Narro1 Author Orcid Image ;   Pablo Ferri1 Author Orcid Image ;   Alba Gutiérrez-Sacristán2 Author Orcid Image ;   Juan M García-Gómez1 Author Orcid Image ;   Carlos Sáez1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

David Fernández-Narro   1 , MSc ;   Pablo Ferri   1 , PhD ;   Alba Gutiérrez-Sacristán   2 , PhD ;   Juan M García-Gómez   1 , PhD ;   Carlos Sáez   1 , PhD

1 Biomedical Data Science Lab, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, Valencia, Valencia, Spain

2 Department of Biomedical Informatics, Harvard Medical School, Harvard University, Boston, MA, United States

Corresponding Author:

  • David Fernández-Narro, MSc
  • Biomedical Data Science Lab
  • Instituto Universitario de Tecnologías de la Información y Comunicaciones
  • Universitat Politècnica de València
  • Camino de Vera s/n
  • Valencia, Valencia 46022
  • Spain
  • Phone: 34 96 387 70 00 ext 75278
  • Email: dfernar@upv.es