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A Survey on Medical Text Mining

by Revathi M Nair, Sindhu L.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 108 - Number 15
Year of Publication: 2014
Authors: Revathi M Nair, Sindhu L.
10.5120/18985-0423

Revathi M Nair, Sindhu L. . A Survey on Medical Text Mining. International Journal of Computer Applications. 108, 15 ( December 2014), 5-11. DOI=10.5120/18985-0423

@article{ 10.5120/18985-0423,
author = { Revathi M Nair, Sindhu L. },
title = { A Survey on Medical Text Mining },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 108 },
number = { 15 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 5-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume108/number15/18985-0423/ },
doi = { 10.5120/18985-0423 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:43:02.769369+05:30
%A Revathi M Nair
%A Sindhu L.
%T A Survey on Medical Text Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 108
%N 15
%P 5-11
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Medical diagnosis is considered as an important yet complicated task that needs to be executed accurately and efficiently. The automation of this system will be very useful for the medical field. Due to recent technology advances, large masses of medical data are available. These large data contain valuable information for diagnosing diseases. Text mining techniques are using to extract useful patterns from these mass data. It provides a user- oriented approach to the novel and hidden patterns in the data. This paper intends to provide the survey of various medical text mining techniques used in medical field. The purpose of this survey is to obtain a most suitable text mining technique for the medical data.

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Index Terms

Computer Science
Information Sciences

Keywords

Information Extraction Summarization Clustering Classification Topic Tracking Information Visualization Concept Linkage Association Rule Mining Question Answering.

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