Back

Automated evaluation of the left-sided heart volumes using machine learning during stress echocardiography: a multicenter stress echo 2030 study

10 May 2023 (08:00 - 20:00)
Organised by:
Congress Presentation Part of: Artificial intelligence 2 Artificial Intelligence EACVI Premium Access EACVI 2023

About the speaker

Photo
Doctor Arnas Karuzas

Lithuanian University of Health Sciences, Kaunas (Lithuania)

7 More presentations in this session

Presentation thumbnail
Machine learning for the generation of personalized image analysis protocol in echocardiography: a pilot study in arterial hypertension
Associate Professor N. Duchateau (Villeurbanne, FR)
Abstract Slides
Presentation thumbnail
Comparison of the accuracy and reproducibility of AI based echocardiography and CMR analysis for cardiac function assessment in oncology patients at risk of cardiotoxicity
Doctor B. Dowsing (London, GB)
Abstract Slides
Presentation thumbnail
Evaluating the feasibility of using artificial intelligence for right ventricle function analysis in a routine clinical setting
Doctor Z. Dindane (Giessen, DE)
Abstract Slides
Presentation thumbnail
Artificial intelligence-based point-of-care lung ultrasound for screening Covid-19 pneumoniae: comparison with CT scans
Doctor T. Kaneko (Tokyo, JP)
Abstract Slides
Presentation thumbnail
Deep-learning based prediction of peak oxygen uptake in athletes using 2D echocardiographic videos
Mr A. Szijarto (Budapest, HU)
Abstract Slides

Access the full session

Session thumbnail
Artificial intelligence 2

The Event

Event poster

EACVI 2023

10 May - 12 May 2023
You may be interested in
thumbnail
Congress Presentation
Real-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study
thumbnail
Congress Session
Evolutions in arrythmia and syncope management
thumbnail
Congress Presentation
State-of-the-art lecture on artificial intelligence guiding clinical diagnosis: from imaging to ECG

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources