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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">PAR</journal-id><journal-title-group><journal-title>Proceedings of Anticancer Research</journal-title></journal-title-group><issn>2208-3545</issn><eissn>2208-3553</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/par.v9i1.9458</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Advances in Artificial Intelligence for Predicting Breast Cancer Using Chest CT Scans</title><url>https://artdesignp.com/journal/PAR/9/1/10.26689/par.v9i1.9458</url><author>SunJingxiang,ZhangGuang</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>9</volume><issue>1</issue><history><date date-type="pub"><published-time>2025-02-13</published-time></date></history><abstract>Breast cancer is the most common malignant tumor among women worldwide, with its incidence and mortality ranking first among all cancers. Early diagnosis and treatment significantly improve prognosis and reduce disease-related mortality. Chest computed tomography (CT), a routine examination for physical assessments and hospitalized patients, can screen for the presence of breast nodules and provide an initial assessment of malignancy risk. In recent years, artificial intelligence (AI) has advanced rapidly in the medical field. Studies have demonstrated that the sensitivity and accuracy of chest CT in diagnosing breast cancer are enhanced through the application of AI methods. This article explores the research progress in breast cancer diagnosis utilizing artificial intelligence based on chest CT examinations.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Hussain A, Gordon-Dixon A, Almusawy H, et al., 2010, The Incidence and Outcome of Incidental Breast Lesions Detected by Computed Tomography. 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