Artificial Intelligence as an Emerging Tool for Cardiologists ^†

In the world of data, there is an urgent need to find ways to extract knowledge and information for improving patient care. Artificial intelligence (AI) is an emerging tool that has the potential to provide cardiologists with new insights and knowledge. The healthcare industry has already begun the digital transformation of vast reams of data (Big Data) that are generated in routine clinical practice. AI has the potential to make a significant impact on healthcare by improving the efficiency of clinical care, providing personalized treatment, and identifying new disease biomarkers. Machine learning (ML) and deep learning (DL) are AI techniques that utilize large datasets and computational power for analysis and decision making. There are three main ML techniques: supervised learning, unsupervised learning, and reinforcement learning. Another functional AI service that has been presented is natural language processing (NLP), and it is applicable for analyzing patient documentation. In this paper, the scope of AI workflow, the most often used algorithms, and their performance metrics are explained. Explainable artificial intelligence (XAI) has a prominent potential to be a useful tool for clinicians as it provides full transparency into an AI model’s decision-making process, but few applications have been reviewed. In this paper, the challenges and limitations of AI in cardiology are discussed in terms of ethical, methodological, and legal issues. Furthermore, the successful establishment of good practices toward the right development and deployment of automated ML-based systems will ensure a regulatory framework that can strengthen patients’ trust in AI/ML-based clinical decision support systems.