Artificial Intelligence in Cardiovascular and Thoracic Anesthesia

Abstract

Recent breakthroughs in artificial intelligence (AI) have particularly shone in cardiothoracic anesthesia, where its ability to efficiently analyze complex datasets and process vast amounts of information in mere moments has captured considerable attention. For cardiothoracic anesthesiologists, the challenge of swiftly evaluating myriad variables is paramount to minimizing complications and optimizing patient outcomes. This article explores the current state of AI in cardiac anesthesia, illuminating the compelling evidence supporting its use and charting potential future paths for researchers and clinicians alike. We will also delve into the challenges in this dynamic field and propose inventive concepts for seamlessly integrating AI into future research initiatives.

Keywords: Artificial intelligence; Cardiac anesthesia; Deep learning; Machine learning; Thoracic anesthesia.