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  Published Paper Details:

  Paper Title

THYROID PROBLEM DETECTION USING NAIVE BAYESIAN CLASSIFICATION

  Authors

  Praveen Hugar,  G.Pranay Goud,  K.Vishnu Vardhan,  Mohammed Faizuddin

  Keywords

Hyperthyroidism, Hypothyroidism, TSH, Supervised Learning, Naive Bayesian Classification.

  Abstract


Thyroid disease is a commonly occurring disease. Thyroid disease can result from conditions that cause over-or under-function of the thyroid gland. The overactive thyroid is known as Hyperthyroidism and the underactive thyroid is known as Hypothyroidism. A TSH test is done to find out if your thyroid gland is working the way it should. TSH stands for �Thyroid Stimulating Hormone� and the test measures how much of this hormone is in your blood. However TSH test is not enough to detect all the problems of Thyroid. Additional tests like T3 test and T4 test need to be carried out. A T3 test measures the blood level of the hormone T3 (triiodothyronine), and T4 test measures thyroxin. A Naive Bayes classifier is a probabilistic machine learning model that�s used for classification task by using Bayes theorem of probability. It is a supervised learning algorithm which makes predictions for new data using Bayes theorem. Naive Bayesian Classification is used to classify the given sample and detect the thyroid problem.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2002146

  Paper ID - 192008

  Page Number(s) - 1340-1343

  Pubished in - Volume 8 | Issue 2 | February 2020

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Praveen Hugar,  G.Pranay Goud,  K.Vishnu Vardhan,  Mohammed Faizuddin,   "THYROID PROBLEM DETECTION USING NAIVE BAYESIAN CLASSIFICATION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 2, pp.1340-1343, February 2020, Available at :http://www.ijcrt.org/papers/IJCRT2002146.pdf

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ISSN: 2320-2882
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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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