Improved long-term prognostic value of coronary CT angiography-derived plaque measures and clinical parameters on adverse cardiac outcome using machine learning

Objectives To evaluate the long-term prognostic value of coronary CT angiography (cCTA)-derived plaque measures and clinical parameters on major adverse cardiac events (MACE) using machine learning (ML). Methods Datasets of 361 patients (61.9 ± 10.3 years, 65% male) with suspected coronary artery di...

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Bibliographic Details
Published in:	European radiology Vol. 31; no. 1; pp. 486 - 493
Main Authors:	Tesche, Christian, Bauer, Maximilian J., Baquet, Moritz, Hedels, Benedikt, Straube, Florian, Hartl, Stefan, Gray, Hunter N., Jochheim, David, Aschauer, Theresia, Rogowski, Sebastian, Schoepf, U. Joseph, Massberg, Steffen, Hoffmann, Ellen, Ebersberger, Ullrich
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 2021 Springer Nature B.V
Subjects:	Algorithms Angiography Calcium Cardiac Cardiovascular disease Cardiovascular diseases Computed Tomography Angiography Coronary Angiography Coronary artery Coronary artery disease Coronary Artery Disease - diagnostic imaging Coronary Stenosis - diagnostic imaging Decision trees Diagnostic Radiology Diagnostic systems Female Health risks Heart Heart diseases Humans Imaging Integration Internal Medicine Interventional Radiology Learning algorithms Machine Learning Male Medical imaging Medicine Medicine & Public Health Neuroradiology Parameters Plaque, Atherosclerotic - diagnostic imaging Predictions Predictive Value of Tests Prognosis Radiology Regression analysis Regression models Retrospective Studies Risk analysis Risk Assessment Risk factors Segments Stenosis Tomography, X-Ray Computed Ultrasound Outcome measures Coronary artery disease Machine learning Multidetector computed tomography
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