Back

Unsupervised classification and anomaly detection of stress echocardiograms with deep spatio-temporal autoencoders.

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

About the speakers

Photo
Assistant Professor Brian Loh

Swinburne University of Technology Sarawak Campus, Kuching (Malaysia)

Photo
Professor Patrick Then

Sarawak Artificial Intelligence Centre, Kuching (Malaysia)

3 More presentations in this session

Presentation thumbnail
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)
Presentation thumbnail
Novel machine learning approaches to categorize and predict heart failure after acute myocardial infarction.
Doctor M. Heisler (Essen, DE)
Presentation thumbnail
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)
Slides Video

Access the full session

Session thumbnail
Artificial Intelligence 1

The Event

Event poster

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