CT Radiomic Features and Clinical Biomarkers for Predicting Coronary Artery Disease
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource, 1 online resource.
- Language
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Englisch
- Bibliographic citation
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CT Radiomic Features and Clinical Biomarkers for Predicting Coronary Artery Disease ; volume:15 ; number:1 ; day:6 ; month:2 ; year:2023 ; pages:238-253 ; date:1.2023
Cognitive Computation ; 15, Heft 1 (6.2.2023), 238-253, 1.2023
- Creator
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Militello, Carmelo
Prinzi, Francesco
Sollami, Giulia
Rundo, Leonardo
La Grutta, Ludovico
Vitabile, Salvatore
- Contributor
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SpringerLink (Online service)
- DOI
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10.1007/s12559-023-10118-7
- URN
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urn:nbn:de:101:1-2023090709130648426583
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:56 AM CEST
Data provider
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Associated
- Militello, Carmelo
- Prinzi, Francesco
- Sollami, Giulia
- Rundo, Leonardo
- La Grutta, Ludovico
- Vitabile, Salvatore
- SpringerLink (Online service)
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Nomogram for predicting major bleeding after off-pump coronary artery bypass grafting
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Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms
Predicting the presence of coronary artery disease by transesophageal echocardiography
Introducing Circulating Vasculature-Related Transcripts as Biomarkers in Coronary Artery Disease
Cardiac biomarkers for detection of coronary artery disease in the community
Predicting clinically unrecognized coronary artery disease: use of two- dimensional echocardiography
Predicting coronary artery disease: a comparison between two data mining algorithms
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