文章基本信息

标题：Machine Learning in Early Genetic Detection of Multiple Sclerosis Disease: A Survey
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作者：Nehal M. Ali ; Mohamed Shaheen ; Mai S. Mabrouk 等
期刊名称：International Journal of Computer Science & Information Technology (IJCSIT)
印刷版ISSN：0975-4660
电子版ISSN：0975-3826
出版年度：2020
卷号：12
期号：5
页码：1-18
DOI：10.5121/ijcsit.2020.12501
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Multiple sclerosis disease is a main cause of non-traumatic disabilities and one of the most common neurological disorders in young adults over many countries. In this work, we introduce a survey study of the utilization of machine learning methods in Multiple Sclerosis early genetic disease detection methods incorporating Microarray data analysis and Single Nucleotide Polymorphism data analysis and explains in details the machine learning methods used in literature. In addition, this study demonstrates the future trends of Next Generation Sequencing data analysis in disease detection and sample datasets of each genetic detection method was included .in addition, the challenges facing genetic disease detection were elaborated.
关键词：Multiple sclerosis;Machine learning;Microarray;Single Nucleotide Polymorphism;early disease detection;Next Generation Sequencing