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

Applications of AI (323) Machine Learning (2199) Clinical Information and Decision Making (2037) Clinical Informatics (1410) Patient Monitoring and Anesthesia Information Management Systems (21) Imaging Informatics (322) Intensive Care Unit (ICU) (166)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67144, first published .
Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

Authors of this article:

Mahmudur Rahman1 Author Orcid Image ;   Jifan Gao2 Author Orcid Image ;   Kyle A Carey3 Author Orcid Image ;   Dana P Edelson3 Author Orcid Image ;   Askar Afshar1 Author Orcid Image ;   John W Garrett2, 4 Author Orcid Image ;   Guanhua Chen2 Author Orcid Image ;   Majid Afshar1, 2 Author Orcid Image ;   Matthew M Churpek1, 2 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Singthongchai J, Wangkhamhan T. Adaptive Normalization Enhances the Generalization of Deep Learning Model in Chest X-Ray Classification. Journal of Imaging 2025;12(1):14 View
  2. Kim J. Explainable deep learning-based multiclass classification of foot radiographs into normal, plantar fasciitis, and flatfoot. Clinical Imaging 2026;131:110724 View

Conference Proceedings

  1. Gonthina S, Shahna Amrilly S, Maddur T, Lakshmi Akella P. 2025 IEEE 22nd India Council International Conference (INDICON). Adaptive Cross-View Attention with Interpretable Bidirectional Lightweight Sequencing for Chest Radiography View