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Official PDF TranslationChinese Journal of New Drugs

Artificial Intelligence in Chronic Obstructive Pulmonary Disease: A Systematic Review and Meta-Analysis of Diagnostic and Prognostic Accuracy

Authors: ZHANG Wei; LI Ming; WANG Fang; CHEN Jing; LIU Yang; ZHAO Lei; SUN Hong; ZHOU Qiang; WU Na; XU Dan

DOI: pub_80__articleID_432Status: Verified Translated Edition
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Key Findings in This Report

• AI models demonstrate high diagnostic accuracy for COPD with pooled sensitivity of 0.89 and specificity of 0.87, and an AUC of 0.94. • Prognostic models show good performance with a pooled C-index of 0.82, indicating effective risk stratification. • Deep learning and imaging-based models outperform traditional machine learning and clinical data models. • High risk of bias and lack of external validation in most studies highlight the need for standardized reporting and validation.