使用支持向量机的护理自由式文本分类

2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI:10.1109/GrC.2007.131

M. Nii, Shigeru Ando, Yutaka Takahashi, A. Uchinuno, R. Sakashita

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引用次数: 28

摘要

护理质量的提高在医疗领域具有十分重要的意义。目前，通过使用Web应用程序从日本的许多医院收集护理自由式文本(护理数据)。一些护理专家对收集到的数据进行评估，以提高护理质量。为了评估护理数据，专家们需要仔细阅读所有的自由式文本。然而，由于数据库中的护理数据数量庞大，专家很难对数据进行评估。为了减少护理数据评估的工作量，提出了一种基于支持向量机(SVM)的分类系统。

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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Nursing-Care Freestyle Text Classification Using Support Vector Machines

The nursing care quality improvement is very important in the medical field. Currently, nursing-care freestyle texts (nursing-care data) are collected from many hospitals in Japan by using Web applications. Some nursing-care experts evaluate the collected data to improve nursing care quality. For evaluating the nursing-care data, experts need to read all freestyle texts carefully. However, it is a hard task for an expert to evaluate the data because of huge number of nursing-care data in the database. In order to reduce workloads evaluating nursing-care data, we propose a support vector machine(SVM) based classification system.

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2007 IEEE International Conference on Granular Computing (GRC 2007)

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