使用临床文件重要性估计器优化基于agent的临床报告检索系统

Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems Pub Date : 2013-06-20 DOI:10.1109/CBMS.2013.6627843

J. Patriarca-Almeida, Bruno Santos, R. Correia

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引用次数: 2

摘要

OPTIM项目旨在通过预测临床文件的相关性来优化电子健康记录(EHR)的图形用户界面，并在特定时间为给定用户提供相关文件的排名列表。在本文中，我们将描述与报表检索和关联分配相关的系统体系结构的一部分，重点是使用OPTIM项目的web服务层对基于代理的报表检索系统(MAID)进行优化。利用优化后的检索方法对MAID原型机进行了仿真测试。在执行的模拟中，分类器每秒能够对10个报告进行评级。在EHR界面中包含一个基于临床相关性的报告评级，通过数学模型计算，可以潜在地提高EHR的可用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Using a clinical document importance estimator to optimize an agent-based clinical report retrieval system

The OPTIM project aims to optimize the graphical user interface of an electronic health record (EHR) by predicting clinical documents' relevance and provide a ranked list of relevant documents for the given user at a certain time. In this paper we will describe part of the system architecture pertaining to report retrieval and relevance assignment, focusing on the optimization of an agent based report retrieval system (MAID) using the webservice layer of the OPTIM project. The prototype of MAID using the optimized retrieval was tested in a simulated environment. In the executed simulations the classifier was able to rate 10 reports per second. Including a report rating in the EHR interface based on clinical relevance calculated by mathematical models can potentially improve the usability of the EHR.

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来源期刊

Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems

CiteScore

3.10

自引率

0.00%

发文量