A
Abdullah Alshahrani
Researcher at King Saud University
Publications - 46
Citations - 609
Abdullah Alshahrani is an academic researcher from King Saud University. The author has contributed to research in topics: Medicine & Bond strength. The author has an hindex of 7, co-authored 32 publications receiving 189 citations. Previous affiliations of Abdullah Alshahrani include Robert Gordon University.
Papers
More filters
Journal ArticleDOI
E-Learning perception and satisfaction among health sciences students amid the COVID-19 pandemic.
Maria Shakoor Abbasi,Naseer Ahmed,Batool Sajjad,Abdullah Alshahrani,Sumera Saeed,Shaur Sarfaraz,Rana S Al-Hamdan,Fahim Vohra,Tariq Abduljabbar +8 more
TL;DR: As the COVID-19 lockdown eases, there is a need for improvement in the methods employed in E-learning and more blended learning among healthcare students is recommended.
Journal ArticleDOI
Advanced Deep Learning-Based Computational Offloading for Multilevel Vehicular Edge-Cloud Computing Networks
Mashael Khayyat,Ibrahim A. Elgendy,Ammar Muthanna,Abdullah Alshahrani,Soltan Abed Alharbi,Andrey Koucheryavy +5 more
TL;DR: This paper presents an advanced deep learning-based computational offloading algorithm for multilevel vehicular edge-cloud computing networks and proposes a distributed deep learning algorithm to find the near-optimal computational offload decisions in which a set of deep neural networks are used in parallel.
Journal ArticleDOI
Management of caries affected dentin (CAD) with resin modified glass ionomer cement (RMGIC) in the presence of different caries disinfectants and photosensitizers.
Abdullah Alshahrani,Eisha Abrar,Ahmed M Maawadh,Rana S Al-Hamdan,Thamer Almohareb,Yasser F. AlFawaz,Mustafa Naseem,Fahim Vohra,Tariq Abduljabbar +8 more
TL;DR: Bond strength of RMGIC bonded to CHX disinfected caries affected dentin with was highest among study groups, and use of MB in Photo-biomodulation showed lowest shear bond strength outcomes.
Journal ArticleDOI
A systematic review of the adoption and acceptance of eHealth in Saudi Arabia: Views of multiple stakeholders.
TL;DR: Findings from this systematic review may help key professionals to address the current challenges and barriers and prioritise the main areas for improvement in eHealth field in Saudi Arabia.
Journal ArticleDOI
A Topical Review on Machine Learning, Software Defined Networking, Internet of Things Applications: Research Limitations and Challenges
Imran,Zeba Ghaffar,Abdullah Alshahrani,Muhammad Fayaz,Ahmed Mohammed Alghamdi,Jeonghwan Gwak +5 more
TL;DR: A topical survey of the application and impact of software-defined networking on the Internet of things networks, carried out from the different perspectives ofSoftware-based Internet of Things networks, including wide-area networks, edge networks, and access networks.