Deep learning based CT images for lung function prediction in patients with chronic obstructive pulmonary disease.

ABSTRACT:

Background

The World Health Organization predicts that by 2030, chronic obstructive pulmonary disease (COPD) will be the third leading cause of death and the seventh leading cause of morbidity worldwide. Pulmonary function tests (PFT) are the gold standard for COPD diagnosis. Since COPD is an incurable disease that takes a considerable amount of time to diagnose, even by an experienced specialist, it becomes important to provide an analysis of abnormalities in a simple manner. Although many deep learning (DL) methods based on computed tomography (CT) have been developed to identify COPD, the pathological changes of COPD based on CT are multi-dimensional and highly spatially heterogeneous, and their predictive performance still needs to be improved.

Objective

The purpose of t

SUBMITTER: Li R 

PROVIDER: S-EPMC12542279 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature