Artificial intelligence in cardiovascular medicine: An exoskeleton for perception, reasoning and action

Abstract

Cardiovascular diseases are a leading cause of morbidity and death, necessitating advanced tools for early diagnosis and personalized care. Artificial intelligence could contribute to transform cardiology through a Perception, Reasoning and Action framework. In the Perception phase, artificial intelligence can improve data acquisition. The Reasoning stage involves artificial intelligence-driven data analysis, integrating large datasets to support clinical decision-making and personalized treatment plans. In the Action phase, artificial intelligence optimizes therapeutic interventions, automates clinical workflows and enhances patient engagement. Artificial intelligence might therefore free up time for cardiologists to focus more on direct patient care and less on data acquisition and analysis, although their supervision remains essential. This review also addresses the technical and ethical challenges of artificial intelligence, including quality of datasets, algorithmic bias, the need for explainable artificial intelligence and data privacy, while exploring future perspectives, such as quantum computing and interdisciplinary collaboration. By addressing these challenges, artificial intelligence has the potential to revolutionize cardiology by enhancing diagnostic precision, advancing risk prediction, optimizing healthcare delivery and improving therapeutic outcomes on a global scale.

Keywords: Artificial intelligence; Cardiology; Clinical decision support; Data acquisition; Machine learning.