Muhammad Usman
- Artificial Intelligence top 5%
- Cognitive Neuroscience top 10%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Signal Processing top 5%
- Co-authors
- A.C.M. FongSimon FongSyed Muhammad UsmanMuhammad AfzaalSajid Ali KhanAyyaz HussainMuhammad AzeemAzhar Mahmood
- Topics
- Data Mining Algorithms and Applications (8 papers)Sentiment Analysis and Opinion Mining (7 papers)Artificial Intelligence in Healthcare (5 papers)
- Partner nations
- PakistanUnited StatesMacao
In The Last Decade
Muhammad Usman
54 papers receiving 798 citations
Peers
Comparison fields: 5 of 112
- Artificial Intelligence 244
- Cognitive Neuroscience 179
- Computer Vision and Pattern Recognition 162
- Information Systems 144
- Signal Processing 110
Countries citing papers authored by Muhammad Usman
This map shows the geographic impact of Muhammad Usman'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 Usman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Usman more than expected).
Fields of papers citing papers by Muhammad Usman
This network shows the impact of papers produced by Muhammad Usman. 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 Usman. The network helps show where Muhammad Usman may publish in the future.
Co-authorship network of co-authors of Muhammad Usman
This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Usman. A scholar is included among the top collaborators of Muhammad Usman 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 Muhammad Usman. Muhammad Usman 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 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 7 | |
| 6 | 1 | |
| 7 | 38 | |
| 8 | 27 | |
| 9 | 2 | |
| 10 | 6 | |
| 11 | 21 | |
| 12 | 62 | |
| 13 | Multi-Level Mining of Association Rules from Warehouse Schema | 1 |
| 14 | 28 | |
| 15 | Multi-Level Mining and Visualization of Informative Association Rules. | 2 |
| 16 | 9 | |
| 17 | 7 | |
| 18 | 16 | |
| 19 | 10 | |
| 20 | 26 |
About Muhammad Usman
Muhammad Usman is a scholar working on Health Information Management, Information Systems and Modeling and Simulation, having authored 59 papers that have together received 863 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (8 papers), Sentiment Analysis and Opinion Mining (7 papers) and Artificial Intelligence in Healthcare (5 papers). The work is most often cited by research in Health Information Management (83 citations), Signal Processing (110 citations) and Cognitive Neuroscience (179 citations). Muhammad Usman has collaborated with scholars based in Pakistan, United States and Macao. Frequent co-authors include A.C.M. Fong, Simon Fong, Syed Muhammad Usman, Muhammad Afzaal, Sajid Ali Khan, Ayyaz Hussain, Muhammad Azeem, Azhar Mahmood, Xiao Zhang and Ran Zhang. Their work appears in journals such as IEEE Communications Magazine, Industrial Marketing Management and Heliyon.
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.