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An Experimental Study of Applying Machine Learning in Prediction of Thyroid Disease

Hetal Patel1

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-1 , Page no. 130-133, Jan-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i1.130133

Online published on Jan 31, 2019

Copyright © Hetal Patel . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Hetal Patel, “An Experimental Study of Applying Machine Learning in Prediction of Thyroid Disease,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.130-133, 2019.

MLA Style Citation: Hetal Patel "An Experimental Study of Applying Machine Learning in Prediction of Thyroid Disease." International Journal of Computer Sciences and Engineering 7.1 (2019): 130-133.

APA Style Citation: Hetal Patel, (2019). An Experimental Study of Applying Machine Learning in Prediction of Thyroid Disease. International Journal of Computer Sciences and Engineering, 7(1), 130-133.

BibTex Style Citation:
@article{Patel_2019,
author = {Hetal Patel},
title = {An Experimental Study of Applying Machine Learning in Prediction of Thyroid Disease},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2019},
volume = {7},
Issue = {1},
month = {1},
year = {2019},
issn = {2347-2693},
pages = {130-133},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3473},
doi = {https://doi.org/10.26438/ijcse/v7i1.130133}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i1.130133}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3473
TI - An Experimental Study of Applying Machine Learning in Prediction of Thyroid Disease
T2 - International Journal of Computer Sciences and Engineering
AU - Hetal Patel
PY - 2019
DA - 2019/01/31
PB - IJCSE, Indore, INDIA
SP - 130-133
IS - 1
VL - 7
SN - 2347-2693
ER -

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Abstract

New advancements have made it workable for an extensive variety of individuals – including humanities and sociology scholastics, advertisers, legislative associations, instructive foundations – to deliver, share, collaborate and arrange data. Monstrous informational collections that were once dark and particular are being amassed and made effectively open. The Huge volumes of heterogeneous therapeutic information these days expanding and easily obtainable from various healthcare organizations. Nowadays, the Thyroid disease is one of the common diseases found in human. The Thyroid hormones created by the thyroid organ to help the control of the body`s digestion. Because of the variations from the norm of thyroid capacity, there might be a lower production of thyroid hormone, which is known as hypothyroidism, or higher production of thyroid hormone, which is known as hyperthyroidism. In this paper, an examination of thyroid disease is carried out by performing experiment of various Machine Learning algorithms techniques such as Naïve Bayes, Support Vector Machine, Multiclass Classifier, Logistic and K Nearest Neighbour. The informational index utilized for this investigation on hypothyroid is taken from UCI information store. The experiment is also completed with WEKA and RConsole. The comparison of various parameters are done and as a result the execution and investigation of different grouping calculation is determined. In the result, it is found that Multiclass Classifier gives preferable exactness over other embraced calculations.

Key-Words / Index Term

Machine Learning, Health Care, Thyroid Disease, Prediction

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