Manar Ahmed Hamza
- Artificial Intelligence top 5%
- AI in cancer detection 12
- Sentiment Analysis and Opinion Mining 9
- Advanced Text Analysis Techniques 8
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- IoT and Edge/Fog Computing 13
- Network Security and Intrusion Detection 10
- Signal Processing top 5%
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- Context-Aware Activity Recognition Systems 9
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- COVID-19 diagnosis using AI 11
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- Brain Tumor Detection and Classification 9
- Co-authors
- Fahd N. Al‐WesabiAnwer Mustafa HilalAbu Sarwar ZamaniMesfer Al DuhayyimAbdelwahed MotwakelIshfaq YaseenMohammed RizwanullahMarwa Obayya
- Journals
- Computers, materials & continua/Computers, materials & continua (Print) (67 papers)IEEE Access (13 papers)Applied Sciences (6 papers)
- Partner nations
- Saudi ArabiaEgyptYemen
In The Last Decade
Manar Ahmed Hamza
132 papers receiving 944 citations
Peers
Comparison fields: 5 of 126
- Health Information Management 59
- Artificial Intelligence 333
- Computer Networks and Communications 226
- Signal Processing 105
- Computer Vision and Pattern Recognition 199
Countries citing papers authored by Manar Ahmed Hamza
This map shows the geographic impact of Manar Ahmed Hamza's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Manar Ahmed Hamza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manar Ahmed Hamza more than expected).
Fields of papers citing papers by Manar Ahmed Hamza
This network shows the impact of papers produced by Manar Ahmed Hamza. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Manar Ahmed Hamza. The network helps show where Manar Ahmed Hamza may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Manar Ahmed Hamza, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 12 | |
| 4 | 2023 | 5 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 31 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 14 | |
| 10 | 2023 | 10 | |
| 11 | 2023 | 12 | |
| 12 | 2023 | 10 | |
| 13 | 2023 | 1 | |
| 14 | 2023 | 11 | |
| 15 | 2023 | 29 | |
| 16 | 2023 | 9 | |
| 17 | 2022 | 2 | |
| 18 | 2022 | 13 | |
| 19 | 2022 | 4 | |
| 20 | 2022 | 3 |
About Manar Ahmed Hamza
Manar Ahmed Hamza is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Neurology and Health Information Management, having authored 140 papers that have together received 998 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (13 papers), AI in cancer detection (12 papers), COVID-19 diagnosis using AI (11 papers), Network Security and Intrusion Detection (10 papers), Brain Tumor Detection and Classification (9 papers), Sentiment Analysis and Opinion Mining (9 papers), Context-Aware Activity Recognition Systems (9 papers) and Advanced Text Analysis Techniques (8 papers). The work is most often cited by research in Health Information Management (59 citations), Artificial Intelligence (333 citations), Computer Networks and Communications (226 citations), Signal Processing (105 citations) and Computer Vision and Pattern Recognition (199 citations). Manar Ahmed Hamza has collaborated with scholars based in Saudi Arabia, Egypt and Yemen. Frequent co-authors include Fahd N. Al‐Wesabi, Anwer Mustafa Hilal, Abu Sarwar Zamani, Mesfer Al Duhayyim, Abdelwahed Motwakel, Ishfaq Yaseen, Mohammed Rizwanullah, Marwa Obayya, Jaber S. Alzahrani and Amani Abdulrahman Albraikan. Their work appears in journals such as Computers, materials & continua/Computers, materials & continua (Print), IEEE Access, Applied Sciences, Cancers and Sustainability.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.