Faten S. Alamri

46 papers and 276 indexed citations i.

About

Faten S. Alamri is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Faten S. Alamri has authored 46 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Faten S. Alamri’s work include AI in cancer detection (5 papers), COVID-19 diagnosis using AI (4 papers) and Brain Tumor Detection and Classification (4 papers). Faten S. Alamri is often cited by papers focused on AI in cancer detection (5 papers), COVID-19 diagnosis using AI (4 papers) and Brain Tumor Detection and Classification (4 papers). Faten S. Alamri collaborates with scholars based in Saudi Arabia, Pakistan and Egypt. Faten S. Alamri's co-authors include Tanzila Saba, Amjad Rehman, Tariq Mahmood, Muhammad Mujahid, Shahid Naseem, Muhammad Saeed, Suliman Mohamed Fati, Mubbasher Munir, Hamiden Abd El‐Wahed Khalifa and Noman Arshed and has published in prestigious journals such as Scientific Reports, International Journal of Hydrogen Energy and Expert Systems with Applications.

In The Last Decade

Co-authorship network of co-authors of Faten S. Alamri i

Fields of papers citing papers by Faten S. Alamri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Countries citing papers authored by Faten S. Alamri

Since Specialization
Citations

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).

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.

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2025