From Data to Clinical Decisions: A Review of Artificial Intelligence and Modern Technologies in Cardiovascular Care

Background: Cardiovascular diseases remain the leading cause of death worldwide and represent a major clinical, social, and economic burden. The traditional model of care is based mainly on medical visits and office-based measurements, whereas many risk factors and symptoms develop in the patient’s everyday environment. Methods: This article is a narrative and systematizing review. The literature was searched using terms related to cardiovascular diseases, digital health, artificial intelligence, machine learning, wearable devices, telemonitoring, heart failure, cardiac imaging, prevention, risk assessment, and electronic health records. Results: Digital technologies can support many areas of cardiovascular care. Artificial intelligence may assist in ECG interpretation, arrhythmia detection, identification of left ventricular dysfunction, and analysis of imaging studies. Wearable devices, mobile applications, and telemonitoring enable long-term monitoring of heart rhythm, physical activity, and selected risk factors; however, their results require clinical interpretation. Conclusions: Modern technologies have great potential in the prevention, diagnosis, and monitoring of cardiovascular diseases, but they should support rather than replace physicians’ clinical judgment. They provide the greatest value when they are validated and integrated into a well-organized care pathway.