Faten S. Alamri
- Artificial Intelligence top 10%
- Neurology top 10%
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition top 10%
- Health Information Management top 5%
- Co-authors
- Tanzila SabaAmjad RehmanTariq MahmoodMuhammad MujahidShahid NaseemAyesha JabbarTeg AlamMuhammad Saeed
- Topics
- AI in cancer detection (6 papers)COVID-19 diagnosis using AI (5 papers)Brain Tumor Detection and Classification (5 papers)
- Partner nations
- Saudi ArabiaPakistanEgypt
In The Last Decade
Faten S. Alamri
39 papers receiving 504 citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Artificial Intelligence 164
- Neurology 125
- Radiology, Nuclear Medicine and Imaging 109
- Computer Vision and Pattern Recognition 105
- Health Information Management 47
Countries citing papers authored by Faten S. Alamri
This map shows the geographic impact of Faten S. Alamri'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 Faten S. Alamri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Faten S. Alamri more than expected).
Fields of papers citing papers by Faten S. Alamri
This network shows the impact of papers produced by Faten S. Alamri. 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 Faten S. Alamri. The network helps show where Faten S. Alamri may publish in the future.
Co-authorship network of co-authors of Faten S. Alamri
This figure shows the co-authorship network connecting the top 25 collaborators of Faten S. Alamri. A scholar is included among the top collaborators of Faten S. Alamri 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 Faten S. Alamri. Faten S. Alamri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 28 | |
| 8 | 2 | |
| 9 | 11 | |
| 10 | Harnessing the power of radiomics and deep learning for improved breast cancer diagnosis with multiparametric breast mammographybreakdown → | 60 |
| 11 | 0 | |
| 12 | 6 | |
| 13 | 0 | |
| 14 | 2 | |
| 15 | 9 | |
| 16 | 60 | |
| 17 | 16 | |
| 18 | 42 | |
| 19 | 2 | |
| 20 | 47 |
About Faten S. Alamri
Faten S. Alamri is a scholar working on Human-Computer Interaction, Statistics and Probability and Statistics, Probability and Uncertainty, having authored 52 papers that have together received 527 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), COVID-19 diagnosis using AI (5 papers) and Brain Tumor Detection and Classification (5 papers). The work is most often cited by research in Neurology (125 citations), Health Information Management (47 citations) and Health Informatics (11 citations). Faten S. Alamri has collaborated with scholars based in Saudi Arabia, Pakistan and Egypt. Frequent co-authors include Tanzila Saba, Amjad Rehman, Tariq Mahmood, Muhammad Mujahid, Shahid Naseem, Amjad Rehman, Ayesha Jabbar, Teg Alam, Muhammad Saeed and Suliman Mohamed Fati. Their work appears in journals such as Scientific Reports, International Journal of Hydrogen Energy and Expert Systems with Applications.
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.