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Accurate Asthma-COPD Overlap Classification via Deep Transfer Learning in Medical Image Segmentation
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Accurate Asthma-COPD Overlap Classification via Deep Transfer Learning in Medical Image Segmentation
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Journal Article
Accurate Asthma-COPD Overlap Classification via Deep Transfer Learning in Medical Image Segmentation
2026
Overview
Differentiating asthma from chronic obstructive pulmonary disease (COPD) remains challenging in clinical practice, and asthma-COPD overlap (ACO) lacks universally accepted diagnostic criteria. In this study, we propose a chest computed tomography (CT) image segmentation framework based on deep transfer learning to support imaging-assisted ACO-related classification as a proof-of-concept approach. Experiments were performed in a single-center cohort of patients with asthma, COPD, and ACO. Model performance was evaluated using classification accuracy and segmentation Dice similarity coefficient against expert-annotated reference masks. In addition, lung function parameters, inflammatory biomarkers, and ACT/CAT scores were summarized to characterize cohort profiles and assist clinical interpretation; these variables were not predicted by the AI model. The proposed approach achieved the highest ACO classification accuracy (93.21%), outperforming NUS-PSL (85.43%) and PRE-1000C (86.92%). These findings suggest potential utility for imaging-assisted ACO-related classification within this internal single-center evaluation. Further multi-center external validation and robustness analyses are warranted before conclusions regarding stability and generalizability can be made.
Publisher
Dove Press,Dove Medical Press
Subject
/ Asthma-Chronic Obstructive Pulmonary Disease Overlap Syndrome - classification
/ Asthma-Chronic Obstructive Pulmonary Disease Overlap Syndrome - diagnostic imaging
/ Asthma-Chronic Obstructive Pulmonary Disease Overlap Syndrome - physiopathology
/ Female
/ Humans
/ Male
/ Pulmonary Disease, Chronic Obstructive - classification
/ Pulmonary Disease, Chronic Obstructive - diagnostic imaging
/ Pulmonary Disease, Chronic Obstructive - physiopathology
/ Radiographic Image Interpretation, Computer-Assisted - methods
