biostudies-literatureGallone GPoC Launchpad567-576https://www.ebi.ac.uk/biostudies/studies/S-EPMC12282367biostudies-literatureUnknown6(4)<h4>Aims</h4>To develop a deep-learning-based system for recognition of subclinical atherosclerosis on a plain frontal chest X-ray.<h4>Methods and results</h4>A deep-learning algorithm to predict coronary artery calcium (CAC) score (the AI-CAC model) was developed on 460 chest X-ray (80% training cohort, 20% internal validation cohort) of primary prevention patients [58.4% male, median age 63 (51-74) years] with available paired chest X-ray and chest computed tomography (CT) indicated for any clinical reason and performed within 3 months. The CAC score calculated on chest CT was used as ground truth. The model was validated on a temporally independent validation cohort of 90 patients from the same institution (external validation). The diagnostic accuracy of the AI-CAC model assessed by thEuropean heart journal. Digital healthDetection of subclinical atherosclerosis by image-based deep learning on chest X-ray.PMC12282367N 120128—2022.3195Fiandrotti AGrangetto MBarbano CAFonio PDe Filippo ODepaoli AIannaccone MGorrini PVisciano MBruno AD'Ascenzo FDe Ferrari GMPresta AIodice FTore DGallone GSerafini AHughes JGrosso Marra WfalseDetection of subclinical atherosclerosis by image-based deep learning on chest X-ray.<h4>Aims</h4>To develop a deep-learning-based system for recognition of subclinical atherosclerosis on a plain frontal chest X-ray.<h4>Methods and results</h4>A deep-learning algorithm to predict coronary artery calcium (CAC) score (the AI-CAC model) was developed on 460 chest X-ray (80% training cohort, 20% internal validation cohort) of primary prevention patients [58.4% male, median age 63 (51-74) years] with available paired chest X-ray and chest computed tomography (CT) indicated for any clinical reason and performed within 3 months. The CAC score calculated on chest CT was used as ground truth. The model was validated on a temporally independent validation cohort of 90 patients from the same institution (external validation). The diagnostic accuracy of the AI-CAC model assessed by th2025-01-01T00:00:00Z2025 Jul2026-03-18T14:02:08.571Z2025-08-23T03:06:42.11ZS-EPMC122823674070313310.1093/ehjdh/ztaf033