G Ital Cardiol (Rome). 2026 Jan;27(1):18-27. doi: 10.1714/4618.46266.
ABSTRACT
Cardiovascular diseases remain the leading cause of morbidity and mortality worldwide, exerting a substantial burden on healthcare systems. Their management requires multidisciplinary approaches, continuity of care, and advanced monitoring tools. Artificial intelligence (AI) has recently emerged as a transformative resource, owing to its ability to analyze large, heterogeneous datasets and generate accurate predictive models. Techniques such as machine learning, deep learning, and natural language processing, combined with multimodal data (electronic health records, imaging, wearable devices, sensors), can enable earlier diagnosis, dynamic risk stratification, and personalized therapies. Furthermore, the integration of AI with telemedicine and digital therapeutics provides new opportunities for remote monitoring, clinical decision support, and patient empowerment, with significant potential to improve clinical outcomes, optimize healthcare resources, and reduce hospitalizations. However, challenges remain, including algorithmic bias, lack of interpretability, ethical and legal concerns, and the need for adequate training of healthcare professionals. The recent adoption of the European AI Act establishes stricter regulatory standards to ensure safety and transparency, though it may slow down large-scale implementation. In conclusion, AI represents a pivotal innovation in cardiovascular medicine, provided it is embedded into validated clinical pathways, supported by scientific evidence, and embraced by clinicians. The future of digital cardiology will rely on the ability to develop predictive, personalized, and patient-centered healthcare models.
PMID:41441829 | DOI:10.1714/4618.46266