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

Artificial Intelligence (2129) Machine Learning (2076) Pulmonology, COPD (195) Respiratory Medicine (157) Clinical Information and Decision Making (1915)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69785, first published .
Deep Learning–Based Chronic Obstructive Pulmonary Disease Exacerbation Prediction Using Flow-Volume and Volume-Time Curve Imaging: Retrospective Cohort Study

Deep Learning–Based Chronic Obstructive Pulmonary Disease Exacerbation Prediction Using Flow-Volume and Volume-Time Curve Imaging: Retrospective Cohort Study

Deep Learning–Based Chronic Obstructive Pulmonary Disease Exacerbation Prediction Using Flow-Volume and Volume-Time Curve Imaging: Retrospective Cohort Study

Authors of this article:

Eun-Tae Jeon1 Author Orcid Image ;   Heemoon Park2 Author Orcid Image ;   Jung-Kyu Lee2 Author Orcid Image ;   Eun Young Heo2 Author Orcid Image ;   Chang Hoon Lee3 Author Orcid Image ;   Deog Kyeom Kim2 Author Orcid Image ;   Dong Hyun Kim4 Author Orcid Image ;   Hyun Woo Lee2 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Wang M, Li L, Feng M, Liu Z. Advances in artificial intelligence applications for the management of chronic obstructive pulmonary disease. Frontiers in Medicine 2025;12 View

Conference Proceedings

  1. Vara J, J P. 2025 7th International Conference on Inventive Material Science and Applications (ICIMA). A Review on COPD Prediction using Convolutional Neural Networks: Approaches, Challenges and Future Directions View