Amira S. Ashour
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Biomedical Engineering top 5%
- Electrical and Electronic Engineering top 10%
- Radiology, Nuclear Medicine and Imaging top 5%
- Co-authors
- Nilanjan DeyFuqian ShiValentina Emilia BălaşSimon FongSuresh Chandra SatapathySankhadeep ChatterjeeJoão Manuel R. S. TavaresR. Simon Sherratt
- Topics
- Digital Imaging for Blood Diseases (16 papers)AI in cancer detection (15 papers)Cutaneous Melanoma Detection and Management (14 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessIEEE Transactions on Biomedical Engineering
In The Last Decade
Amira S. Ashour
161 papers receiving 3.9k citations
Peers
Comparison fields: 5 of 183
- Artificial Intelligence 1.1k
- Computer Vision and Pattern Recognition 1.1k
- Biomedical Engineering 563
- Electrical and Electronic Engineering 526
- Radiology, Nuclear Medicine and Imaging 515
Countries citing papers authored by Amira S. Ashour
This map shows the geographic impact of Amira S. Ashour'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 Amira S. Ashour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amira S. Ashour more than expected).
Fields of papers citing papers by Amira S. Ashour
This network shows the impact of papers produced by Amira S. Ashour. 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 Amira S. Ashour. The network helps show where Amira S. Ashour may publish in the future.
Co-authorship network of co-authors of Amira S. Ashour
This figure shows the co-authorship network connecting the top 25 collaborators of Amira S. Ashour. A scholar is included among the top collaborators of Amira S. Ashour 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 Amira S. Ashour. Amira S. Ashour 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 | 1 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 18 | |
| 9 | 5 | |
| 10 | 9 | |
| 11 | 1 | |
| 12 | Optimal PID Parameters based Ant Colony Optimization Algorithm of Power System with Non-Linearity and Boiler Dynamics | 1 |
| 13 | 60 | |
| 14 | 35 | |
| 15 | 63 | |
| 16 | 3 | |
| 17 | 8 | |
| 18 | 20 | |
| 19 | 16 | |
| 20 | 11 |
About Amira S. Ashour
Amira S. Ashour is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Biophysics, having authored 165 papers that have together received 4.1k indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (16 papers), AI in cancer detection (15 papers) and Cutaneous Melanoma Detection and Management (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Artificial Intelligence (1.1k citations) and Neurology (251 citations). Amira S. Ashour has collaborated with scholars based in Egypt, India and China. Frequent co-authors include Nilanjan Dey, Fuqian Shi, Valentina Emilia Bălaş, Simon Fong, Suresh Chandra Satapathy, Sankhadeep Chatterjee, João Manuel R. S. Tavares, R. Simon Sherratt, Yanhui Guo and V. Rajinikanth. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Biomedical Engineering.
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.