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Automated electronic health record frailty assessment for older cardiac patients

26 August 2022 (15:30 - 15:40)
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Congress Presentation Part of: Digital health innovation: from artificial intelligence to clinical decision support m-Health & Mobile Apps ESC Professional Premium Access ESC Congress 2022

About the speaker

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Doctor Atul Anand

University of Edinburgh, Edinburgh (United Kingdom of Great Britain & Northern Ireland)

5 More presentations in this session

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Multi-category classification of left ventricle ejection fraction using a convolutional neural network
Professor R. Carter (Jacksonville, US)
Abstract Slides Video
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Smartphone-based remote monitoring in chronic heart failure: patient & clinician user experience, impact on patient engagement and quality of life.
Miss A. Auton (London, GB)
Abstract Slides Video
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Evaluation of cardiac function and 30-day clinical outcome with synchronized analysis of phonocardiogram and electrocardiogram in patients with acute myocardial infarction
Doctor W. Zhang (Shanghai, CN)
Abstract Slides
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Estimating prevalence and characteristics of statin intolerance among high and very high cardiovascular risk patients in Germany between 2017-2020
Professor K. Parhofer (Munich, DE)
Abstract Slides Video
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Deep learning-based electrocardiogram analysis detecting paroxysmal atrial fibrillation during sinus rhythm in patients with cryptogenic stroke : validation study using implantable cardiac monitoring
Assistant Professor K. Jeon (Seongnam, KR)
Abstract Slides Video

Access the full session

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Digital health innovation: from artificial intelligence to clinical decision support

The Event

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ESC Congress 2022

26 August 2022 15:30 CET
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ESC 365 is supported by

novartis Explore sponsored resources