Data mining approach for diagnosing migraine headache
Publish Year: 1397
نوع سند: مقاله کنفرانسی
زبان: English
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ICIORS11_106
تاریخ نمایه سازی: 30 دی 1397
Abstract:
Data mining is an essential process, where intelligent methods are applied to extract data patterns, and it is the process of discovering interesting patterns and knowledge from large amount of data. In wide range of medical fields, it has been greatly expanded in recent years. This paper was designed to use three algorithms in the data mining field for recognition of migraine headache. Decision Tree, Naive-Bayes classification and Random Decision Forest techniques are used for migraine diagnosis. Performance of these techniques has been compared and Random Forest technique is observed as the best diagnosis with 93.1% accuracy.
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Authors
Monire khayamnia
Ph.D. candidate of Applied Mathematics, Tehran Payame Noor University, Tehran, Iran
Mohammadreza Yazdchi
Associate Professor, Department of Biomedical Engineering , Faculty of Engineering , University of Isfahan, Isfahan, Iran
Aghile Heidari
Associate Professor, Department of Mathematics, School of Mathematics, Mashhad Payame Noor University, Mashhad,Iran