Title : The past, present and future of AI in cardiology
Abstract:
Artificial Intelligence (AI) is transforming cardiovascular medicine by enhancing diagnostic accuracy, treatment selection, and patient outcomes. Machine learning algorithms now analyse complex cardiac imaging with superhuman precision, detecting subtle patterns in echocardiograms, cardiac MRI, and coronary CT angiography that may elude human interpretation. Deep learning models demonstrate remarkable capability in predicting cardiovascular events from multimodal data, integrating clinical parameters, imaging findings, and genomic markers to stratify patient risk with greater accuracy than traditional scoring systems. In clinical practice, AI-powered clinical decision support systems assist physicians in treatment selection, medication management, and identifying patients requiring intervention, while wearable technologies enabled by AI algorithms provide continuous cardiac monitoring and early detection of arrhythmias. The emergence of AI-guided robotic systems shows promise for enhancing precision in complex cardiac procedures. Despite these advances, significant challenges persist, including addressing algorithmic bias, ensuring appropriate validation across diverse populations, maintaining data privacy, and integrating AI tools effectively into clinical workflows. As implementation expands, ongoing evaluation of clinical outcomes and cost-effectiveness remains essential to determine AI's true value in cardiovascular care.
