The future of artificial intelligence in cardiovascular monitoring

Cardiovascular monitoring is essential for managing hemodynamic instability and preventing complications in critically ill patients. Conventional monitoring approaches are limited by predefined thresholds, dependence on clinician expertise, and a lack of adaptability to individual patients. The aim of this review is to explore recent findings about the use of artificial intelligence (AI) in cardiovascular monitoring.

AI has the potential to transform monitoring in critical care through the automated real-time analysis of extensive, high-resolution datasets, and can facilitate early detection of patient deterioration, minimize false alarms, and support patient clustering for tailored therapeutic strategies. These innovations facilitate a shift toward precision medicine, tailoring treatments based on physiological and temporal data patterns. Moreover, wearable devices can further enhance real-time patient surveillance and risk stratification, extending intensivist monitoring beyond the ICU. Despite advantages, challenges persist, including algorithm generalizability, issues with patient consent and data privacy, and the current lack of external validation. Overcoming these barriers is essential for realizing the full potential of AI in critical care and hemodynamic monitoring.

The integration of continuous high-resolution monitoring with AI real-time applications has the potential to transform hemodynamic assessment, enhance clinical decision-making, and improve safety and clinical outcomes.