Usman Qamar
- Artificial Intelligence top 1%
- Information Systems top 0.5%
- Health Information Management top 0.2%
- Computer Networks and Communications top 5%
- Computational Theory and Mathematics top 2%
- Co-authors
- Saba BashirFarhan Hassan KhanAyesha KhalidMuhammad Summair RazaMuhammad Younus JavedMuhammad UsmanAli HassanSaad Rehman
- Topics
- Data Mining Algorithms and Applications (26 papers)Rough Sets and Fuzzy Logic (21 papers)Sentiment Analysis and Opinion Mining (19 papers)
- Partner nations
- PakistanUnited StatesUnited Kingdom
In The Last Decade
Usman Qamar
133 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Artificial Intelligence 1.3k
- Information Systems 915
- Health Information Management 396
- Computer Networks and Communications 310
- Computational Theory and Mathematics 214
Countries citing papers authored by Usman Qamar
This map shows the geographic impact of Usman Qamar'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 Usman Qamar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Usman Qamar more than expected).
Fields of papers citing papers by Usman Qamar
This network shows the impact of papers produced by Usman Qamar. 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 Usman Qamar. The network helps show where Usman Qamar may publish in the future.
Co-authorship network of co-authors of Usman Qamar
This figure shows the co-authorship network connecting the top 25 collaborators of Usman Qamar. A scholar is included among the top collaborators of Usman Qamar 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 Usman Qamar. Usman Qamar 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 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 35 | |
| 9 | 2 | |
| 10 | 29 | |
| 11 | 8 | |
| 12 | 5 | |
| 13 | 10 | |
| 14 | 107 | |
| 15 | Terrorist Group Prediction Using Data Classification | 11 |
| 16 | An Approach to Detect Spam Emails by Using Majority Voting | 1 |
| 17 | Inference Engine for Classification of Expert Systems Using Keyword Extraction Technique | 1 |
| 18 | 23 | |
| 19 | 51 | |
| 20 | 44 |
About Usman Qamar
Usman Qamar is a scholar working on Health Information Management, Information Systems and Artificial Intelligence, having authored 141 papers that have together received 2.5k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (26 papers), Rough Sets and Fuzzy Logic (21 papers) and Sentiment Analysis and Opinion Mining (19 papers). The work is most often cited by research in Health Information Management (396 citations), Information Systems (915 citations) and Artificial Intelligence (1.3k citations). Usman Qamar has collaborated with scholars based in Pakistan, United States and United Kingdom. Frequent co-authors include Saba Bashir, Farhan Hassan Khan, Ayesha Khalid, Muhammad Summair Raza, Muhammad Younus Javed, Muhammad Usman, Ali Hassan, Saad Rehman, Farhan Riaz and Abdul Wahab Muzaffar. Their work appears in journals such as PLoS ONE, IEEE Access and Pattern Recognition.
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.