Research and Implementation for Rural Medical Information Extraction Method

被引：0

作者：

Gao, Yutong ^{[1
]}

Song, Feifan ^{[2
,3
]}

Xie, Xiaqing ^{[4
]}

Geng, Shengnan ^{[3
]}

Tang, Wenling ^{[3
,5
]}

机构：

[1] Natl Taipei Univ Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan

[2] Beijing Univ Posts & Telecommun, Sch Econ & Management, Beijing 100088, Peoples R China

[3] Minist Educ, Key Lab Trustworthy Distributed Comp & Serv BUPT, Beijing, Peoples R China

[4] Beijing Univ Posts & Telecommun Lib, Beijing, Peoples R China

[5] Beijing Univ Posts & Telecommun, Sch Comp Sci, Beijing 100088, Peoples R China

来源：

COMPUTATIONAL INTELLIGENCE AND INTELLIGENT SYSTEMS, (ISICA 2015) | 2016年 / 575卷

关键词：

Rural medical; Information extraction; Naive bayes parallelization;

D O I：

10.1007/978-981-10-0356-1_59

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Currently, the input of rural clinic system in china is the symptom from patients' descriptions. However, the existing problems in patients' descriptions are irregular and colloquial description, too much irrelevant information, etc. We need to use information extraction technology to extract more useful information as the input information of the following procedure for better matching between symptom and illness and enhancing the accuracy of the clinic. We designed an information extraction method for rural clinic using open source tools. Based on the machine learning methods, we extract time and degree information was extracted from the patients' descriptions. We designed and implement parallelization of the algorithms to speed up the response.

引用

页码：562 / 571

页数：10

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