Artificial intelligence in cardiothoracic monitoring and echocardiography

Purpose of review This review describes the recent advancements of artificial intelligence (AI) in cardiothoracic anesthesia monitoring. Recent findings The application of AI in cardiothoracic anesthesia monitoring has potential to affect all phases of perioperative care – from preoperative testing and risk stratification to postoperative evaluation and advances in echocardiography image acquisition and interpretation. While these developments are promising, they remain in the early stages of clinical integration and validation. Summary Advances in machine learning and natural language processing are expected to play an increasingly significant role in the monitoring and management of cardiothoracic surgery patients. As these technologies evolve, they hold the potential to enhance the precision, efficiency, and personalization of care. However, as AI becomes more integrated into clinical decision-making, it is imperative that care models remain grounded in the core principles of patient-centeredness and safety.