文章基本信息

标题：MLTDD : Use of Machine Learning Techniques for Diagnosis of Thyroid Gland Disorder
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作者：Izdihar Al-muwaffaq ; Zeki Bozkus
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2016
卷号：6
期号：5
页码：67-73
DOI：10.5121/csit.2016.60507
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Machine learning algorithms are used to diagnosis for many diseases after very importantimprovements of classification algorithms as well as having large data sets and high performingcomputational units. All of these increased the accuracy of these methods. The diagnosis ofthyroid gland disorders is one of the application for important classification problem. Thisstudy majorly focuses on thyroid gland medical diseases caused by underactive or overactivethyroid glands. The dataset used for the study was taken from UCI repository. Classification ofthis thyroid disease dataset was a considerable task using decision tree algorithm. The overallprediction accuracy is 100% for training and in range between 98.7% and 99.8% for testing. Inthis study, we developed the Machine Learning tool for Thyroid Disease Diagnosis (MLTDD),an Intelligent thyroid gland disease prediction tool in Python, which can effectively help tomake the right decision, has been designed using PyDev, which is python IDE for Eclipse.
关键词：Machine Learning; Thyroid diseases; CRT decision tree algorithm; PyDev; Python IDE.