%0 Journal Article %1 alimachine %A Ali, Nehal M. %A Shaheen, Mohamed %A Mabrouk, Mai S. %A AboRezka, Mohamed A. %D 2020 %J International Journal of Computer Science & Information Technology (IJCSIT) %K Generation Machine Microarray Multiple Next Nucleotide Polymorphism Sequencing. Single detection disease early learning sclerosis %N 5 %P 01 - 18 %R 10.5121/ijcsit.2020.12501 %T Machine Learning in Early Genetic Detection of Multiple Sclerosis Disease: A Survey %U https://aircconline.com/abstract/ijcsit/v12n5/12520ijcsit01.html %V 12 %X 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.

@article{alimachine, abstract = {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. }, added-at = {2020-11-10T07:49:59.000+0100}, author = {Ali, Nehal M. and Shaheen, Mohamed and Mabrouk, Mai S. and AboRezka, Mohamed A.}, biburl = {https://www.bibsonomy.org/bibtex/2a3cdfbdb747d9d7d27fe29c4c1b544f4/shamerjose}, doi = {10.5121/ijcsit.2020.12501}, interhash = {84def2f4d5666e4977c0a62b634cdf40}, intrahash = {a3cdfbdb747d9d7d27fe29c4c1b544f4}, journal = {International Journal of Computer Science & Information Technology (IJCSIT) }, keywords = {Generation Machine Microarray Multiple Next Nucleotide Polymorphism Sequencing. Single detection disease early learning sclerosis}, month = {October}, number = 5, pages = {01 - 18}, timestamp = {2020-11-10T07:49:59.000+0100}, title = {Machine Learning in Early Genetic Detection of Multiple Sclerosis Disease: A Survey }, url = {https://aircconline.com/abstract/ijcsit/v12n5/12520ijcsit01.html}, volume = 12, year = 2020 }