Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Moustafa Salem"'
Autor:
Mohammed Ahmed Sadeq, Reem Mohamed Farouk Ghorab, Mohamed Hady Ashry, Ahmed Mohamed Abozaid, Haneen A. Banihani, Moustafa Salem, Mohammed Tawfiq Abu Aisheh, Saad Abuzahra, Marina Ramzy Mourid, Mohamad Monif Assker, Mohammed Ayyad, Mostafa Hossam El Din Moawad
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Large language models (LLMs) like ChatGPT have potential applications in medical education such as helping students study for their licensing exams by discussing unclear questions with them. However, they require evaluation on these complex
Externí odkaz:
https://doaj.org/article/d014a3575f6e483381be26536146c33e
Autor:
Moustafa Salem, Walid Emam, Yusra Tashkandy, Mohamed Ibrahim, M. Masoom Ali, Hafida Goual, Haitham M. Yousof
Publikováno v:
Symmetry, Vol 15, Iss 7, p 1356 (2023)
The idea of symmetry, which is used to describe the shape of a probability distribution, is a key concept in the theory of probability. The use of symmetric and asymmetric distributions is common in statistical inference, decision-making, and probabi
Externí odkaz:
https://doaj.org/article/40423d4a424d4f649c162465463a9a07
Autor:
Moustafa Salem, Mohamed G. Khalil
Publikováno v:
Pakistan Journal of Statistics and Operation Research. :167-186
Time series are essential for anticipating various claims payment applications. For insurance firms to prevent significant losses brought on by potential future claims, the future values of predicted claims are crucial. Additionally, the ideal parame
Autor:
Yousof, Moustafa Salem, Walid Emam, Yusra Tashkandy, Mohamed Ibrahim, M. Masoom Ali, Hafida Goual, Haitham M.
Publikováno v:
Symmetry; Volume 15; Issue 7; Pages: 1356
The idea of symmetry, which is used to describe the shape of a probability distribution, is a key concept in the theory of probability. The use of symmetric and asymmetric distributions is common in statistical inference, decision-making, and probabi
Autor:
Moustafa Salem, Mohamed G. Khalil
Publikováno v:
Pakistan Journal of Statistics and Operation Research. :427-435
Support Vector Regression (SVR) formulates is an optimization problem to learn a regression function that maps from input predictor variables to output observed response values. The SVR is useful because it balances model complexity and prediction er
Publikováno v:
Journal of Computational and Theoretical Nanoscience. 16:2687-2694
Publikováno v:
The FASEB Journal. 27
Publikováno v:
The FASEB Journal. 21
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