This narrative review systematically summarizes the current applications of artificial intelligence (AI) in thoracic radiology. AI has been applied to a wide range of thoracic diseases, including lung cancer screening, pulmonary nodule detection and classification, interstitial lung diseases (ILD), chronic obstructive pulmonary disease (COPD), and COVID-19 pneumonia. Particularly, deep learning-based segmentation and classification techniques have enabled automated CT analysis, improving diagnostic accuracy and consistency. In ILD, AI assists in pattern classification and quantitative assessment, while in COPD, it is used for quantifying low attenuation areas (LAA). During the COVID-19 pandemic, AI was rapidly deployed for diagnosis and severity prediction. The review also addresses challenges such as regulatory hurdles, clinical integration limitations, and potential data bias.
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