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

26 August 2022 (08:00 - 19:30)
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Congress Presentation Part of: New horizons in plaque imaging Plaque Imaging ESC Professional Premium Access ESC Congress 2022

About the speaker

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Doctor Nehal Mehta

George Washington University, Washington, DC (United States of America)

6 More presentations in this session

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Automatic quantification of plaque progression dynamics as assessed by serial coronary computed tomography angiography using scan-quality-based vessel specific thresholds.
Doctor F. Van Driest (Leiden, NL)
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Cardiometabolic predictors of quantitative high-risk plaque features in a diverse patient population
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
Doctor M. Kruk (Warsaw, PL)
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Artificial intelligence-enabled comprehensive coronary phenotyping in patients with suspected CAD
Doctor J. Viegas (Lisbon, PT)
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Radiomics-based analysis by machine learning techniques improves characterization of functionally significant coronary lesions
Mr G. Kalykakis (Athens, GR)
Abstract Slides

Access the full session

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New horizons in plaque imaging

The Event

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ESC Congress 2022

26 August - 29 August 2022
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ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources