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A Hybrid Group Search Optimizer with Opposition-Based Learning and Differential Evolution Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Research and Implementation for Rural Medical Information Extraction Method

Authors : Yutong Gao, Feifan Song, Xiaqing Xie, Shengnan Geng, Wenling Tang

Published in: Computational Intelligence and Intelligent Systems

Publisher: Springer Singapore

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Abstract

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.

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previous chapter User Oriented Semi-automatic Method of Constructing Domain Ontology
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Metadata
Title
Research and Implementation for Rural Medical Information Extraction Method
Authors
Yutong Gao
Feifan Song
Xiaqing Xie
Shengnan Geng
Wenling Tang
Copyright Year
2016
Publisher
Springer Singapore
Book
Computational Intelligence and Intelligent Systems

Print ISBN: 978-981-10-0355-4

Electronic ISBN: 978-981-10-0356-1

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-981-10-0356-1_59

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