An Empirical Model for Thyroid Disease Classification using Evolutionary Multivariate Bayseian Prediction Method

An Empirical Model for Thyroid Disease Classification using Evolutionary Multivariate Bayseian Prediction Method

K. Geetha

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S. Santhosh Baboo

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Periyar University

An Empirical Model for Thyroid Disease Classification using Evolutionary Multivariate Bayseian Prediction Method

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Abstract

Thyroid diseases are widespread worldwide. In India too, there is a significant problems caused due to thyroid diseases. Various research studies estimates that about 42 million people in India suffer from thyroid diseases [4]. There are a number of possible thyroid diseases and disorders, including thyroiditis and thyroid cancer. This paper focuses on the classification of two of the most common thyroid disorders are hyperthyroidism and hypothyroidism among the public. The National Institutes of Health (NIH) states that about 1% of Americans suffer from Hyperthyroidism and about 5% suffer from Hypothyroidism. From the global perspective also the classification of thyroid plays a significant role. The conditions for the diagnosis of the disease are closely linked, they have several important differences that affect diagnosis and treatment. The data for this research work is collected from the UCI repository which undergoes preprocessing. The preprocessed data is multivariate in nature. Curse of Dimensionality is followed so that the available 21 attributes is optimized to 10 attributes using Hybrid Differential Evolution Kernel Based Navie Based algorithm. The subset of data is now supplied to Kernel Based Naïve Bayes classifier algorithm in order to check for the fitness.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

K. Geetha. 2016. \u201cAn Empirical Model for Thyroid Disease Classification using Evolutionary Multivariate Bayseian Prediction Method\u201d. Global Journal of Computer Science and Technology - H: Information & Technology GJCST-H Volume 16 (GJCST Volume 16 Issue H1).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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H.2.8

Submission ReceivedDecember 13, 2015
Peer Review Double Blind
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Accepted January 5, 2016
Published January 15, 2016

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v1.2

Issue date

March 4, 2016

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Article Matrices

Total Score: 102

Country: India

Subject: Global Journal of Computer Science and Technology - H: Information & Technology

Authors: K. Geetha, S. Santhosh Baboo (PhD/Dr. count: 0)

View Count (all-time): 278

Total Views (Real + Logic): 7373

Total Downloads (simulated): 1913

Publish Date: 2016 03, Fri

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Total Views: 7373

Total Downloads: 1913

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