Mohamed Elaraby
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Radiology, Nuclear Medicine and Imaging
- Information Systems
- Signal Processing
- Co-authors
- Muhammad Abdul-MageedHamdi A. MahmoudTarek Abd El‐HafeezMahmoud Y. ShamsM. Z. RashadOmar M. ElzekiAmena MahmoudHanaa Salem
- Topics
- Natural Language Processing Techniques (6 papers)Topic Modeling (3 papers)AI in cancer detection (3 papers)
- Journals
- Biomedical Signal Processing and ControlMultimedia Tools and ApplicationsBMC Medical Informatics and Decision Making
- Partner nations
- EgyptUnited StatesCanada
In The Last Decade
Mohamed Elaraby
17 papers receiving 283 citations
Hit Papers
Peers
Comparison fields: 5 of 80
- Artificial Intelligence 180
- Computer Vision and Pattern Recognition 45
- Radiology, Nuclear Medicine and Imaging 40
- Information Systems 34
- Signal Processing 22
Countries citing papers authored by Mohamed Elaraby
This map shows the geographic impact of Mohamed Elaraby'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 Mohamed Elaraby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed Elaraby more than expected).
Fields of papers citing papers by Mohamed Elaraby
This network shows the impact of papers produced by Mohamed Elaraby. 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 Mohamed Elaraby. The network helps show where Mohamed Elaraby may publish in the future.
Co-authorship network of co-authors of Mohamed Elaraby
This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Elaraby. A scholar is included among the top collaborators of Mohamed Elaraby based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mohamed Elaraby. Mohamed Elaraby is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 37 | |
| 2 | Feature reduction for hepatocellular carcinoma prediction using machine learning algorithmsbreakdown → | 99 |
| 3 | 9 | |
| 4 | 8 | |
| 5 | 4 | |
| 6 | 22 | |
| 7 | 6 | |
| 8 | 9 | |
| 9 | 6 | |
| 10 | You Tweet What You Speak: A City-Level Dataset of Arabic Dialects | 41 |
| 11 | Deep Models for Arabic Dialect Identification on Benchmarked Data | 40 |
| 12 | 3 | |
| 13 | 8 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 3 | |
| 17 | Design of optimal fuzzy controller for water level of U-Tube steam generator in nuclear power station | 8 |
About Mohamed Elaraby
Mohamed Elaraby is a scholar working on Linguistics and Language, Artificial Intelligence and Health Information Management, having authored 17 papers that have together received 306 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Topic Modeling (3 papers) and AI in cancer detection (3 papers). The work is most often cited by research in Artificial Intelligence (180 citations), Health Informatics (7 citations) and Linguistics and Language (12 citations). Mohamed Elaraby has collaborated with scholars based in Egypt, United States and Canada. Frequent co-authors include Muhammad Abdul-Mageed, Hamdi A. Mahmoud, Tarek Abd El‐Hafeez, Mahmoud Y. Shams, M. Z. Rashad, Omar M. Elzeki, Amena Mahmoud, Hanaa Salem, Diane Litman and Yang Zhong. Their work appears in journals such as Biomedical Signal Processing and Control, Multimedia Tools and Applications and BMC Medical Informatics and Decision Making.
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.