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

Congress Session

About the speaker

Doctor Nehal Mehta

The George Washington University, Washington, DC (United States of America)
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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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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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Radiomics-based analysis by machine learning techniques improves characterization of functionally significant coronary lesions

Speaker: Mr G. Kalykakis (Athens, GR)

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New horizons in plaque imaging

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

26 August - 29 August 2022

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