UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 6
June-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR1906251


Registration ID:
214133

Page Number

745-748

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Title

Symptom based clinical document clustering and Cancer prediction using data mining

Abstract

in this research paper detection of the cancer disease based on the symptoms .Medical records which contains vast amount of data includes unidentified patterns .Storing these vast amount of medical records is very necessary and important. Managing these records helps your work done very easily and faster So here data mining is one of the technique used for managing these records. Data Mining is a technique which is used for mining the data. The term mining means bringing out patterns which are hidden and previously unidentified for better grasp of the particular problem. Several data mining techniques such as the Classification algorithms like , Genetic algorithm, Neural network, Artificial intelligence, Naïve Bayes and Clustering algorithms like SVM, .Hence in this paper we are going to make prediction and it will include part of clustering documents based on the symptoms that patient will provide. So if Symptom based clinical document clustering is done properly then a good report can be presented to the client. Proper symptoms with proper details of the patient must be given to the doctor so that the client or the patient will be aware of the disease on the time and hence the patient can be given the proper treatment. Early detection of cancer plays a very important role in reducing deaths caused by cancer. After that the prediction is done we need to make the document clustering based on the most common cluster we make cluster based on the type of the heterogeneous data sets and The technique which is used is python for the actual data sets implementation and accuracy is calculated through the algorithm for better accuracy

Key Words

clustering, k-mean algorithm, naive Bayes algorithm, prediction

Cite This Article

" Symptom based clinical document clustering and Cancer prediction using data mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.745-748, June-2019, Available :http://www.jetir.org/papers/JETIR1906251.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

" Symptom based clinical document clustering and Cancer prediction using data mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp745-748, June-2019, Available at : http://www.jetir.org/papers/JETIR1906251.pdf

Publication Details

Published Paper ID: JETIR1906251
Registration ID: 214133
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 745-748
Country: Mumbai, Maharashtra, India, maharashtra, mumbai .
Area: Medical Science
ISSN Number: 2349-5162
Publisher: IJ Publication


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