IMPROVING DIAGNOSIS OF CARDIOVASCULAR DISEASES BY ARTIFICIAL INTELLIGENCE IN ELECTROCARDIOGRAPHY

Cardiovascular diseases are the leading cause of death worldwide, and the electrocardiogram (ECG) is an essential tool for diagnosis. However, errors in ECG interpretation are common. Artificial intelligence (AI) has shown promise in improving diagnostic accuracy, outperforming experts in some cases. This study aims to explore how AI can optimize the diagnosis of cardiovascular diseases by ECG and analyze the impact on clinical practice, especially in nursing. OBJECTIVE: To conduct a literature review on the improvement of cardiovascular disease diagnosis through the application of artificial intelligence in electrocardiography, highlighting its contributions to clinical practice and its implications for nursing practice. METHODOLOGY: Literature review using the main databases. RESULTS: The use of AI to analyze medical images, predict cardiac events, interpret electrocardiograms, personalize treatments, monitor patients remotely and optimize cardiac procedures was explored. We also discussed the ethical, regulatory and safety considerations associated with the implementation of AI in clinical practice. CONCLUSIONS: This review highlights the potential of AI in improving cardiology care, while highlighting the importance of addressing ethical challenges and ensuring patient safety.