Zobrazeno 1 - 10 of 43 pro vyhledávání: '"Gehad Ismail Sayed"'
1
Akademický článek
Circulating miRNA’s biomarkers for early detection of hepatocellular carcinoma in Egyptian patients based on machine learning algorithms
Autor: Gehad Ismail Sayed, Mona Solyman, Gamalat El Gedawy, Yasmine S. Moemen, Hassan Aboul-Ella, Aboul Ella Hassanien
Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract Liver cancer, which ranks sixth globally and third in cancer-related deaths, is caused by chronic liver disorders and a variety of risk factors. Despite therapeutic improvements, the prognosis for Hepatocellular Carcinoma (HCC) remains poor,
Externí odkaz: https://doaj.org/article/f2ee6d5529fd45698c916b66cd5fd344
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3
Akademický článek
Air Pollutants Classification Using Optimized Neural Network Based on War Strategy Optimization Algorithm.
Autor: Gehad Ismail Sayed, Aboul Ella Hassanein
Publikováno v: Automatic Control & Computer Sciences; Dec2023, Vol. 57 Issue 6, p600-607, 8p
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5
A novel multilevel thresholding algorithm based on quantum computing for abdominal CT liver images
Autor: Gehad Ismail Sayed
Publikováno v: Evolutionary Intelligence. 16:439-483
Image segmentation is considered one of the important tasks for extracting useful information from an image. Multilevel thresholding image segmentation is one of the effective techniques for image segmentation. The computation time grows exponentiall
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2c7b5ff70806558df42e2e2f4035b64a
https://doi.org/10.1007/s12065-021-00669-9
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7
A novel Chaotic Equilibrium Optimizer Algorithm with S-shaped and V-shaped transfer functions for feature selection
Autor: Mohamed H. Haggag, Ghada Khoriba, Gehad Ismail Sayed
Publikováno v: Journal of Ambient Intelligence and Humanized Computing. 13:3137-3162
Feature selection is considered one of the challenging machine learning tasks. Selecting a subset of relevant features can significantly influence on the classification accuracy and computational time of any machine learning algorithm. This paper int
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::15e12189d4062207774796aa393e7c63
https://doi.org/10.1007/s12652-021-03151-7
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