Thyroid Disease Classification Using Machine Learning Algorithms

Author:

salman Khalid,Sonuç Emrullah

Abstract

Abstract With the vast amount of data and information difficult to deal with, especially in the health system, machine learning algorithms and data mining techniques have an important role in dealing with data. In our study, we used machine learning algorithms with thyroid disease. The goal of this study is to categorize thyroid disease into three categories: hyperthyroidism, hypothyroidism, and normal, so we worked on this study using data from Iraqi people, some of whom have an overactive thyroid gland and others who have hypothyroidism, so we used all of the algorithms. Support vector machines, random forest, decision tree, naïve bayes, logistic regression, k-nearest neighbors, multi-layer perceptron (MLP), linear discriminant analysis. To classification of thyroid disease.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference30 articles.

1. Expert system based on neural fuzzy rules for thyroid diseases diagnosis;Azar;Computer Science, Artificial Intelligence,2012

2. ESTDD: Expert system for thyroid diseases diagnosis;Keles;Expert Syst Appl.,2008

3. Machine learning applications in cancer prognosis and prediction;Kouroua;Computational and Structural Biotechnology Journal,2015

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