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pro vyhledávání: '"Eman Salih Al-Shamery"'
Autor:
Mahmood Khalsan, Mu Mu, Eman Salih Al-Shamery, Suraj Ajit, Lee R. Machado, Michael Opoku Agyeman
Publikováno v:
IEEE Access, Vol 11, Pp 115161-115178 (2023)
In the pursuit of better cancer classification, many studies have been conducted to identify the genes associated with cancer. However, the high dimensionality of gene expression data and the limited relevance of a few genes pose significant challeng
Externí odkaz:
https://doaj.org/article/1c9b3a1372204a889068d28c19d98008
Autor:
Mahmood Khalsan, Lee R. Machado, Eman Salih Al-Shamery, Suraj Ajit, Karen Anthony, Mu Mu, Michael Opoku Agyeman
Publikováno v:
IEEE Access, Vol 10, Pp 27522-27534 (2022)
Machine learning approaches are powerful techniques commonly employed for developing cancer prediction models using associated gene expression and mutation data. This manuscript provides a comprehensive review of recent cancer studies that have emplo
Externí odkaz:
https://doaj.org/article/c29344e941a44159942c0d83f55dcc04
Publikováno v:
Karbala International Journal of Modern Science. 7
Publikováno v:
Karbala International Journal of Modern Science. 6
Publikováno v:
Journal of University of Babylon, Vol 25, Iss 2, Pp 341-348 (2017)
In this research, the shingle algorithm with Jaccard method are employed as a new approach to detect deception in sources in addition to detect plagiarism . Source deception occurs as a result of taking a particular text from a source and relative it