首页> 外文会议>International Conference on Mobile Computing and Ubiquitous Network >Proposal of Anesthetic Dose Prediction Model to Avoid Post-induction Hypotension Using Electronic Anesthesia Records
【24h】

Proposal of Anesthetic Dose Prediction Model to Avoid Post-induction Hypotension Using Electronic Anesthesia Records

机译:关于使用电子麻醉记录避免诱导后低血压的麻醉剂量预测模型的建议

获取原文

摘要

Post-induction hypotension frequently occurred after anesthesia induction. Avoiding post-induction hypotension is important as it is associated with postoperative adverse outcomes. Related studies have shown that the dose of anesthetic induction drugs affects the post-induction hypotension. The purpose of this study is to propose an anesthetic dose that does not cause post-induction hypotension according to the patient's condition. A model for predicting the optimal dose of an anesthetic induction drug is constructed using a regression model which is one of machine learning methods by focusing on electronic anesthesia records. The prediction coefficient of determination 0.5008 was achieved by adjusting the explanatory variables and parameters and using ridge regression.
机译:诱导后低血压经常在麻醉诱导后发生。避免诱导后低血压很重要,因为它与术后不良后果相关。相关研究表明,麻醉诱导药物的剂量会影响诱导后低血压。这项研究的目的是根据患者的病情提出一种不会引起诱导后低血压的麻醉剂量。使用回归模型构建预测麻醉诱导药物最佳剂量的模型,该模型是通过关注电子麻醉记录而成为机器学习方法之一。通过调整解释变量和参数并使用岭回归,可以得出确定的预测系数0.5008。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号