机器学习在术后谵妄预测方面的应用及前景

Application and prospects of machine learning in the prediction of postoperative delirium

术后谵妄(POD)与多种不良预后相关,具有重要的医学和公共卫生意义。不同年龄段的手术人群和手术类型均可发生POD。对POD进行精确预测有助于改善患者预后,而POD的发生与多方面因素有关,现有的预测工具数量有限且在预测能力上存在一定不足。随着人工智能在医学领域应用的兴起,为POD的预测提供了新的方法。文章综述近年来通过人工智能来预测POD的研究现状,揭示了其优缺点,并对未来前景进行讨论,以期为POD的诊疗提供新的思路。

Postoperative delirium(POD)is associated with a variety of poor prognoses and has important medical and public health implications.POD can occur in surgical populations of different ages and types of surgeries.Accurate prediction of POD can help to improve the prognosis of patients.The occurrence of POD is related to multiple factors,and the existing prediction tools are lim‐ited in number and deficient in predictive ability.With the rising use of artificial intelligence in the medical community,new methods for the prediction of POD have been provided.In this review,we summarize the current research on the prediction of POD by artificial intelligence methods in recent years,reveal their advantages and disadvantages,and discuss the prospects for providing new ideas for the diagnosis and treatment of POD.