Unlocking the potential of artificial intelligence in sports cardiology : does it have a role in evaluating athlete's heart?

© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please e-mail: journals.permissionsoup.com..

The integration of artificial intelligence (AI) technologies is evolving in different fields of cardiology and in particular in sports cardiology. Artificial intelligence offers significant opportunities to enhance risk assessment, diagnosis, treatment planning, and monitoring of athletes. This article explores the application of AI in various aspects of sports cardiology, including imaging techniques, genetic testing, and wearable devices. The use of machine learning and deep neural networks enables improved analysis and interpretation of complex datasets. However, ethical and legal dilemmas must be addressed, including informed consent, algorithmic fairness, data privacy, and intellectual property issues. The integration of AI technologies should complement the expertise of physicians, allowing for a balanced approach that optimizes patient care and outcomes. Ongoing research and collaborations are vital to harness the full potential of AI in sports cardiology and advance our management of cardiovascular health in athletes.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:31

Enthalten in:

European journal of preventive cardiology - 31(2024), 4 vom: 04. März, Seite 470-482

Sprache:

Englisch

Beteiligte Personen:

Palermi, Stefano [VerfasserIn]
Vecchiato, Marco [VerfasserIn]
Saglietto, Andrea [VerfasserIn]
Niederseer, David [VerfasserIn]
Oxborough, David [VerfasserIn]
Ortega-Martorell, Sandra [VerfasserIn]
Olier, Ivan [VerfasserIn]
Castelletti, Silvia [VerfasserIn]
Baggish, Aaron [VerfasserIn]
Maffessanti, Francesco [VerfasserIn]
Biffi, Alessandro [VerfasserIn]
D'Andrea, Antonello [VerfasserIn]
Zorzi, Alessandro [VerfasserIn]
Cavarretta, Elena [VerfasserIn]
D'Ascenzi, Flavio [VerfasserIn]

Links:

Volltext

Themen:

Artificial intelligence
Athlete’s heart
Cardiovascular prevention
Deep learning
Journal Article
Machine learning
Sports cardiology

Anmerkungen:

Date Completed 06.03.2024

Date Revised 06.03.2024

published: Print

Citation Status MEDLINE

doi:

10.1093/eurjpc/zwae008

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM366893645