Shaymaa E. Sorour
About
In The Last Decade
Shaymaa E. Sorour
36 papers receiving 297 citations
Hit Papers
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 150
- Computer Science Applications 146
- Information Systems 73
- Neurology 46
- Health Information Management 44
Countries citing papers authored by Shaymaa E. Sorour
This map shows the geographic impact of Shaymaa E. Sorour'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 Shaymaa E. Sorour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaymaa E. Sorour more than expected).
Fields of papers citing papers by Shaymaa E. Sorour
This network shows the impact of papers produced by Shaymaa E. Sorour. 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 Shaymaa E. Sorour. The network helps show where Shaymaa E. Sorour may publish in the future.
Co-authorship network of co-authors of Shaymaa E. Sorour
This figure shows the co-authorship network connecting the top 25 collaborators of Shaymaa E. Sorour. A scholar is included among the top collaborators of Shaymaa E. Sorour 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 Shaymaa E. Sorour. Shaymaa E. Sorour is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 10 | |
| 10 | 5 | |
| 11 | 0 | |
| 12 | 4 | |
| 13 | 6 | |
| 14 | 1 | |
| 15 | 3 | |
| 16 | 3 | |
| 17 | 3 | |
| 18 | 40 | |
| 19 | 9 | |
| 20 | Predicting Student Grade based on Free-style Comments using Word2Vec and ANN by Considering Prediction Results Obtained in Consecutive Lessons. | 20 |
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.