Back

Unraveling the complexity of hypertrophic cardiomyopathy: a machine learning-based radiomics model to predict phenotype and cardiovascular events

13 May 2024 (14:00 - 14:45)
Organised by: Logo
Congress Presentation Part of: Myocardial disease - clinical 7 Hypertrophic Cardiomyopathy HFA Premium Access Heart Failure 2024 Heart Failure Association (HFA)

About the speaker

Photo
Doctor Ines Miranda

Hospital Professor Doutor Fernando Fonseca, Amadora (Portugal)

7 More presentations in this session

Presentation thumbnail
Identification of a novel actin gene mutation, ACTC1 p.Asn94Ile, in a family with cardiomyopathy and conduction disease
Doctor R. Sepp (Szeged, HU)
Abstract Slides Video
Presentation thumbnail
Refining the diagnosis of hypertrophic cardiomyopathy with a machine learning-based radiomics model: a cardiovascular magnetic resonance study
Doctor I. Miranda (Amadora, PT)
Abstract Slides Video
Presentation thumbnail
Different exercise hemodynamic profiles in obstructive and nonobstructive hypertrophic cardiomyopathy: importance of unmasking diastolic dysfunction
Doctor C. Baratto (Bergamo, IT)
Abstract Slides Video
Presentation thumbnail
Cardiac magnetic resonance feature tracking identifies preclinical abnormalities in hypertrophic cardiomyopathy sarcomere gene mutation carriers
Doctor F. Negri (Udine, IT)
Abstract Slides Video
Presentation thumbnail
Machine-learning based radiomics model to predict ventricular arrythmias in patients with hypertrophic cardiomyopathy
Doctor M. Marques Antunes (Lisboa, PT)
Abstract Slides

Access the full session

Session thumbnail
Myocardial disease - clinical 7

The Event

Event poster

Heart Failure 2024

13 May 2024 14:00 CET
You may be interested in
thumbnail
Congress Presentation
Refining the diagnosis of hypertrophic cardiomyopathy with a machine learning-based radiomics model: a cardiovascular magnetic resonance study
thumbnail
Congress Presentation
Machine learning algorithms for predicting arrhythmic events in hypertrophic cardiomyopathy: limited enhancement beyond late gadolinium enhancement
thumbnail
Congress Session
Artificial intelligence, radiomics, and granular cardiovascular magnetic resonance for enhanced cardiac diagnosis

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources