Cardiovascular diseases remain the leading cause of death globally and impose significant economic burdens. The growing prevalence of cardiovascular diseases underscores the need for advanced prevention and management strategies. Artificial intelligence, specifically with machine learning and deep learning, offers transformative potential in cardiology for a wide range of tasks. This thesis explores the application of artificial intelligence in cardiovascular care, focusing on clinical prediction models, integration of multimodal data, and the development of algorithms for specific cardiovascular conditions. Additionally, it addresses the challenges of model validation and real-world applicability, proposing rigorous methodologies for improving artificial intelligence’s role in cardiology care.

Machine learning applications in cardiology / Baj, Giovanni. - (2025 Feb 03).

Machine learning applications in cardiology

BAJ, GIOVANNI
2025-02-03

Abstract

Cardiovascular diseases remain the leading cause of death globally and impose significant economic burdens. The growing prevalence of cardiovascular diseases underscores the need for advanced prevention and management strategies. Artificial intelligence, specifically with machine learning and deep learning, offers transformative potential in cardiology for a wide range of tasks. This thesis explores the application of artificial intelligence in cardiovascular care, focusing on clinical prediction models, integration of multimodal data, and the development of algorithms for specific cardiovascular conditions. Additionally, it addresses the challenges of model validation and real-world applicability, proposing rigorous methodologies for improving artificial intelligence’s role in cardiology care.
3-feb-2025
SCAGNETTO, ARJUNA
BORTOLUSSI, LUCA
BARBATI, GIULIA
37
2023/2024
Settore INF/01 - Informatica
Università degli Studi di Trieste
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3104821
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