Ahmed Sakr
- Artificial Intelligence
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition
- Physiology
- Cardiology and Cardiovascular Medicine
- Co-authors
- Paweł PławiakMohamed HammadNaglaa F. SolimanAbdelhamied A. AteyaMehdhar S. A. M. Al-GaashaniRyszard TadeusiewiczHanaa BadranMaher A. Kamel
- Topics
- Chaos-based Image/Signal Encryption (5 papers)ECG Monitoring and Analysis (4 papers)COVID-19 diagnosis using AI (3 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingArtificial IntelligenceComputer Vision and Pattern Recognition
- Partner nations
- EgyptSaudi ArabiaPoland
In The Last Decade
Ahmed Sakr
12 papers receiving 163 citations
Peers
Comparison fields: 5 of 56
- Artificial Intelligence 58
- Radiology, Nuclear Medicine and Imaging 57
- Computer Vision and Pattern Recognition 26
- Physiology 25
- Cardiology and Cardiovascular Medicine 22
Countries citing papers authored by Ahmed Sakr
This map shows the geographic impact of Ahmed Sakr'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 Ahmed Sakr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ahmed Sakr more than expected).
Fields of papers citing papers by Ahmed Sakr
This network shows the impact of papers produced by Ahmed Sakr. 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 Ahmed Sakr. The network helps show where Ahmed Sakr may publish in the future.
Co-authorship network of co-authors of Ahmed Sakr
This figure shows the co-authorship network connecting the top 25 collaborators of Ahmed Sakr. A scholar is included among the top collaborators of Ahmed Sakr 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 Ahmed Sakr. Ahmed Sakr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 18 | |
| 5 | 12 | |
| 6 | 58 | |
| 7 | 7 | |
| 8 | 23 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 21 | |
| 12 | 1 | |
| 13 | 18 | |
| 14 | A Steganographic Method Based on DCT and New Quantization Technique. | 7 |
| 15 | 1 |
About Ahmed Sakr
Ahmed Sakr is a scholar working on Computer Vision and Pattern Recognition, Cardiology and Cardiovascular Medicine and Radiology, Nuclear Medicine and Imaging, having authored 15 papers that have together received 173 indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (5 papers), ECG Monitoring and Analysis (4 papers) and COVID-19 diagnosis using AI (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (57 citations), Artificial Intelligence (58 citations) and Computer Vision and Pattern Recognition (26 citations). Ahmed Sakr has collaborated with scholars based in Egypt, Saudi Arabia and Poland. Frequent co-authors include Paweł Pławiak, Mohamed Hammad, Naglaa F. Soliman, Abdelhamied A. Ateya, Mehdhar S. A. M. Al-Gaashani, Ryszard Tadeusiewicz, Hanaa Badran, Maher A. Kamel, Maha Elsabaawy and Mohamed Sakr. Their work appears in journals such as Information Sciences, Applied Sciences and Drug Development Research.
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.