海量多参数临床信息数据库的时态搜索引擎

L. Lehman, T. H. Kyaw, G. Clifford, R. Mark
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引用次数: 3

摘要

我们描述了一种新的搜索引擎,它能够快速执行有关多个不规则采样和异步生理参数在许多时间尺度上的梯度和绝对(和相对)值变化的查询。搜索引擎使用梯度边界、变化率和阈值在各种时间尺度上实现多种生理参数的搜索标准。多个信号可以以布尔方式进行搜索和组合,形成复杂的查询。使用预先计算的范围和多尺度梯度来显著减少定位时间事件的搜索时间。我们已经在MATLAB中实现了搜索引擎,并在一个大型多参数重症监护病房数据库(MIMIC II)上测试了该算法。为了说明我们的搜索方法的使用,临床医生开发了一套数值搜索标准,以定位重要病理生理条件的证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A temporal search engine for a massive multi-parameter clinical information database
We describe a novel search engine that is capable of rapid execution of queries concerning changes in the gradients and absolute (and relative) values of multiple irregularly sampled and asynchronous physiological parameters over many time scales. The search engine enables search criteria for multiple physiological parameters using gradient bounds, rates of change, and threshold breeches over various time scales. Multiple signals can be searched and combined in a Boolean manner to form complex queries. Pre-computed ranges and multi-scale gradients are used to significantly reduce the search time for locating temporal events. We have implemented the search engine in MATLAB and tested the algorithm on a massive multi-parameter intensive care unit database (MIMIC II). To illustrate the use of our search approach, a set of numerical search criteria were developed by clinicians to locate evidence for important pathophysiological conditions.
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