Suppr超能文献

患者监测中趋势检测与预测的现状

The present state of trend detection and prediction in patient monitoring.

作者信息

Endresen J, Hill D W

出版信息

Intensive Care Med. 1977 Apr;3(1):15-26. doi: 10.1007/BF01683184.

Abstract

An investigation has been carried out into the suitability of the following techniques for trend detection and forecasting in patient monitoring: Cusum; Trigg's Tracking Signal; The Patient Condition Factor; The Patient Alarm Warning System; Box-Jenkins models and the Harrison-Stevens Bayesian approach. The latter holds considerable promise since it is flexible and can be implemented on a microprocessor. Consideration has also been given to the need for a better knowledge of the statistical properties of the variables to be monitored and the problems of combining trends detected in severable variables.

摘要

针对以下技术在患者监测中的趋势检测和预测适用性展开了一项调查

累积和(Cusum);特里格跟踪信号(Trigg's Tracking Signal);患者状况因子(The Patient Condition Factor);患者警报预警系统(The Patient Alarm Warning System);博克斯-詹金斯模型(Box-Jenkins models)以及哈里森-史蒂文斯贝叶斯方法(the Harrison-Stevens Bayesian approach)。后者颇具前景,因为它具有灵活性且可在微处理器上实现。还考虑到需要更好地了解待监测变量的统计特性以及合并在多个变量中检测到的趋势所存在的问题。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验