Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
GE Healthcare, Waukesha, WI.
J Cardiothorac Vasc Anesth. 2021 Jan;35(1):251-261. doi: 10.1053/j.jvca.2020.08.048. Epub 2020 Aug 24.
Echocardiography is a unique diagnostic tool for intraoperative monitoring and assessment of patients with cardiovascular diseases. However, there are high levels of interoperator variations in echocardiography interpretations that could lead to inaccurate diagnosis and incorrect treatment. Furthermore, anesthesiologists are faced with the additional challenge to interpret echocardiography and make decisions in a limited timeframe from these complex data. The need for an automated, less operator-dependent process that enhances speed and accuracy of echocardiography analysis is crucial for anesthesiologists. Artificial intelligence is playing an increasingly important role in the medical field and could help anesthesiologists analyze complex echocardiographic data while adding increased accuracy and consistency to interpretation. This review aims to summarize practical use of artificial intelligence in echocardiography and discusses potential limitations and challenges in the future for anesthesiologists.
超声心动图是一种用于术中监测和评估心血管疾病患者的独特诊断工具。然而,超声心动图的解释存在很高的操作者间差异,可能导致不准确的诊断和错误的治疗。此外,麻醉师还面临着从这些复杂的数据中进行解释和做出决策的额外挑战。需要一个自动化的、较少依赖操作者的过程,以提高超声心动图分析的速度和准确性,这对麻醉师来说至关重要。人工智能在医学领域的作用越来越重要,它可以帮助麻醉师分析复杂的超声心动图数据,同时提高解释的准确性和一致性。本文旨在总结人工智能在超声心动图中的实际应用,并讨论未来对麻醉师可能存在的局限性和挑战。