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Radiomics-based analysis by machine learning techniques improves characterization of functionally significant coronary lesions

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About the speaker

Mr Georgios-Eleftherios Kalykakis

Academy of Athens Biomedical Research Foundation, Athens (Greece)
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6 more presentations in this session

Automatic quantification of plaque progression dynamics as assessed by serial coronary computed tomography angiography using scan-quality-based vessel specific thresholds.

Speaker: Doctor F. Van Driest (Leiden, NL)

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Application of machine learning to identify top determinants of fibrofatty plaque burden by CCTA in humans with psoriasis

Speaker: Doctor N. Mehta (Washington, DC, US)

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Cardiometabolic predictors of quantitative high-risk plaque features in a diverse patient population

Speaker: Doctor J. Arce (Bronx, US)

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Identification of non-calcified coronary plaque characteristics using machine learning radiomic analysis of non-contrast high-resolution CT

Speaker: Doctor M. Kruk (Warsaw, PL)

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Artificial intelligence-enabled comprehensive coronary phenotyping in patients with suspected CAD

Speaker: Doctor J. Viegas (Lisbon, PT)

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New horizons in plaque imaging

Speakers: Mr G. Kalykakis, Doctor F. Van Driest, Doctor N. Mehta, Doctor J. Arce, Doctor M. Kruk...
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ESC Congress 2022

26 August - 29 August 2022

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