TOWARDS ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSE THYROID PROBLEMS

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A820V

TOWARDS ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSE THYROID PROBLEMS

Dr. V.Sarasvathi
Dr. V.Sarasvathi CMS COLLEGE OF SCIENCE AND COMMERCE
Dr.A.Santhakumaran
Dr.A.Santhakumaran
DOI

Abstract

Medical diagnosis can be viewed as a pattern classification problem: based a set of input features the goal is to classify a patient as having a particular disorder or as not having it. Thyroid hormone problems are the most prevalent problems nowadays. In this paper an artificial neural network approach is developed using a back propagation algorithm in order to diagnose thyroid problems. It gets a number of factors as input and produces an output which gives the result of whether a person has the problem or is healthy. It is found that back propagation algorithm is proved to be having high sensitivity and specificity.

TOWARDS ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSE THYROID PROBLEMS

Medical diagnosis can be viewed as a pattern classification problem: based a set of input features the goal is to classify a patient as having a particular disorder or as not having it. Thyroid hormone problems are the most prevalent problems nowadays. In this paper an artificial neural network approach is developed using a back propagation algorithm in order to diagnose thyroid problems. It gets a number of factors as input and produces an output which gives the result of whether a person has the problem or is healthy. It is found that back propagation algorithm is proved to be having high sensitivity and specificity.

Dr. V.Sarasvathi
Dr. V.Sarasvathi CMS COLLEGE OF SCIENCE AND COMMERCE
Dr.A.Santhakumaran
Dr.A.Santhakumaran

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Dr. V.Sarasvathi. 1970. “. Unknown Journal GJCST Volume 11 (GJCST Volume 11 Issue 5): .

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TOWARDS ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSE THYROID PROBLEMS

Dr. V.Sarasvathi
Dr. V.Sarasvathi CMS COLLEGE OF SCIENCE AND COMMERCE
Dr.A.Santhakumaran
Dr.A.Santhakumaran

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