Oumaima Saidani
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Neurology top 10%
- Radiology, Nuclear Medicine and Imaging
- Computer Networks and Communications
- Co-authors
- Nazik AlturkiMuhammad UmerImran AshrafAla Saleh AlluhaidanRashid JahangirLeila JamelShtwai AlsubaiAbid Ishaq
- Topics
- COVID-19 diagnosis using AI (7 papers)Brain Tumor Detection and Classification (6 papers)Network Security and Intrusion Detection (5 papers)
- Journals
- Scientific ReportsIEEE AccessSensors
- Partner nations
- Saudi ArabiaPakistanSouth Korea
In The Last Decade
Oumaima Saidani
47 papers receiving 497 citations
Peers
Comparison fields: 5 of 110
- Artificial Intelligence 200
- Computer Vision and Pattern Recognition 113
- Neurology 79
- Radiology, Nuclear Medicine and Imaging 67
- Computer Networks and Communications 57
Countries citing papers authored by Oumaima Saidani
This map shows the geographic impact of Oumaima Saidani'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 Oumaima Saidani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oumaima Saidani more than expected).
Fields of papers citing papers by Oumaima Saidani
This network shows the impact of papers produced by Oumaima Saidani. 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 Oumaima Saidani. The network helps show where Oumaima Saidani may publish in the future.
Co-authorship network of co-authors of Oumaima Saidani
This figure shows the co-authorship network connecting the top 25 collaborators of Oumaima Saidani. A scholar is included among the top collaborators of Oumaima Saidani 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 Oumaima Saidani. Oumaima Saidani 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 | 2 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 13 | |
| 7 | 7 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 21 | |
| 11 | 27 | |
| 12 | 28 | |
| 13 | 1 | |
| 14 | 2 | |
| 15 | 31 | |
| 16 | 9 | |
| 17 | 19 | |
| 18 | 2 | |
| 19 | 31 | |
| 20 | Towards Situational Business Process Meta-Modelling. | 2 |
About Oumaima Saidani
Oumaima Saidani is a scholar working on Health Information Management, Neurology and Computer Vision and Pattern Recognition, having authored 58 papers that have together received 521 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (7 papers), Brain Tumor Detection and Classification (6 papers) and Network Security and Intrusion Detection (5 papers). The work is most often cited by research in Health Informatics (13 citations), Neurology (79 citations) and Artificial Intelligence (200 citations). Oumaima Saidani has collaborated with scholars based in Saudi Arabia, Pakistan and South Korea. Frequent co-authors include Nazik Alturki, Muhammad Umer, Imran Ashraf, Ala Saleh Alluhaidan, Rashid Jahangir, Leila Jamel, Shtwai Alsubai, Abid Ishaq, Amel Ksibi and Latifah Almuqren. Their work appears in journals such as Scientific Reports, IEEE Access and Sensors.
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.