Abdul Muneeim Tehame
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Abdul Muneeim Tehame has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Ahmed Barnawi
King Abdulaziz University
1 shared publication - Saad Zia
IT Department, Jeddah Cable Company, Jeddah 31248, Saudi Arabia
1 shared publication - Saleh Bajaba
Department of Business Administration King Abdulaziz University Jeddah Saudi Arabia
1 shared publication - Tarik Alafif
Department of Computer Science, Jamoum University College, Umm Al-Qura University, Jamoum, Saudi Arabia
1 shared publication
Latest Publications
- Open Access
- 27 January 2021
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 18 (3) , 1117
Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions
With many successful stories, machine learning (ML) and deep learning (DL) have been widely used in our everyday lives in a number of ways. They have also been instrumental in tackling the outbreak of Coronavirus (COVID-19), which has been happening around the world. The SARS-CoV-2 virus-induced COVID-19 epidemic has spread rapidly across the world, leading to international outbreaks. The COVID-19 fight to curb the spread of the disease involves most states, companies, and scientific research institutions. In this research, we look at the Artificial Intelligence (AI)-based ML and DL methods for COVID-19 diagnosis and treatment. Furthermore, in the battle against COVID-19, we summarize the AI-based ML and DL methods and the available datasets, tools, and performance. This survey offers a detailed overview of the existing state-of-the-art methodologies for ML and DL researchers and the wider health community with descriptions of how ML and DL and data can improve the status of COVID-19, and more studies in order to avoid the outbreak of COVID-19. Details of challenges and future directions are also provided.
- 27 January 2021
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 18 (3) , 1117
Open AccessMachine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions
With many successful stories, machine learning (ML) and deep learning (DL) have been widely used in our everyday lives in a number of ways. They have also been instrumental in tackling the outbreak of Coronavirus (COVID-19), which has been happening around the world. The SARS-CoV-2 virus-induced COVID-19 epidemic has spread rapidly across the world, leading to international outbreaks. The COVID-19 fight to curb the spread of the disease involves most states, companies, and scientific research institutions. In this research, we look at the Artificial Intelligence (AI)-based ML and DL methods for COVID-19 diagnosis and treatment. Furthermore, in the battle against COVID-19, we summarize the AI-based ML and DL methods and the available datasets, tools, and performance. This survey offers a detailed overview of the existing state-of-the-art methodologies for ML and DL researchers and the wider health community with descriptions of how ML and DL and data can improve the status of COVID-19, and more studies in order to avoid the outbreak of COVID-19. Details of challenges and future directions are also provided.