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Novel machine learning approaches to categorize and predict heart failure after acute myocardial infarction.

5 October 2019 (00:00 - 00:00)
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Congress Presentation Part of: Artificial Intelligence 1 m-Health & Mobile Apps ESC Premium Access Digital Health 2019

About the speaker

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Doctor Martin Heisler

Essen (Germany)

3 More presentations in this session

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Unsupervised classification and anomaly detection of stress echocardiograms with deep spatio-temporal autoencoders.
Assistant Professor B. Loh (Kuching, MY) Professor P. Then (Kuching, MY)
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Development of a decision support tool to predict outcome of coronary CT calcium score and angiography: Study Design and Data Preparation
Miss K. Siegersma (Amsterdam, NL)
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Using GSP and Activity monitors to explore the activity levels and utilization of healthcare services of patients in the first 30-days after discharge from hospital for patients with ACS.
Professor R. Clark (Adelaide, AU)
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Artificial Intelligence 1

The Event

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Digital Health 2019

5 October - 6 October 2019

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources