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Article

Predicting Acute Exacerbation Phenotype in Chronic Obstructive Pulmonary Disease Patients Using VGG-16 Deep Learning.

Respiration; international review of thoracic diseases - 1 Jan 2025

Feng Shengchuan, Zhang Ran, Zhang Wenxiu, Yang Yuqiong, Song Aiqi, Chen Jiawei, Wang Fengyan, Xu Jiaxuan, Liang Cuixia, Liang Xiaoyun, Chen Rongchang, Liang Zhenyu

Abstract excerpt

INTRODUCTION: Exacerbations of chronic obstructive pulmonary disease (COPD) have a significant impact on hospitalizations, morbidity, and mortality of patients. This study aimed to develop a model for predicting acute exacerbation in COPD patients (AECOPD) based on deep-learning (DL) features. METHODS: We performed a retrospective study on 219 patients with COPD who underwent inspiratory and expiratory HRCT...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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PMID: 39047695
DOI: 10.1159/000540383

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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