Muhammad Umer

104 papers and 1.6k indexed citations i.

About

Muhammad Umer is a scholar working on Artificial Intelligence, Information Systems and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Muhammad Umer has authored 104 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Artificial Intelligence, 21 papers in Information Systems and 18 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Muhammad Umer’s work include AI in cancer detection (17 papers), Artificial Intelligence in Healthcare (15 papers) and COVID-19 diagnosis using AI (13 papers). Muhammad Umer is often cited by papers focused on AI in cancer detection (17 papers), Artificial Intelligence in Healthcare (15 papers) and COVID-19 diagnosis using AI (13 papers). Muhammad Umer collaborates with scholars based in Pakistan, Saudi Arabia and South Korea. Muhammad Umer's co-authors include Saima Sadiq, Saleem Ullah, Michele Nappi, Gyu Sang Choi, Arif Mehmood, Imran Ashraf, Seyedali Mirjalili, Abid Ishaq, Vaibhav Rupapara and Zainab Imtiaz and has published in prestigious journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Co-authorship network of co-authors of Muhammad Umer i

Fields of papers citing papers by Muhammad Umer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Umer. 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 Muhammad Umer. The network helps show where Muhammad Umer may publish in the future.

Countries citing papers authored by Muhammad Umer

Since Specialization
Citations

This map shows the geographic impact of Muhammad Umer'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 Muhammad Umer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Umer 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2025