Mohd Usama
Impact in
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- Artificial Intelligence in Healthcare
- Artificial Intelligence top 5%
- Sentiment Analysis and Opinion Mining
- AI in cancer detection
- Topic Modeling
- Advanced Text Analysis Techniques
- Machine Learning in Healthcare
Papers in
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- Sentiment Analysis and Opinion Mining 4
- Topic Modeling 4
- AI in cancer detection 3
- Machine Learning in Healthcare 3
- Text and Document Classification Technologies 2
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- Artificial Intelligence in Healthcare 3
- Co-authors
- Belal Ahmad (11 shared papers)M. Shamim Hossain (4 shared papers)Ghulam Muhammad (3 shared papers)Saqib Qamar (4 shared papers)Parvez Ahmad (5 shared papers)Ran Zheng (2 shared papers)Hai Jin (2 shared papers)Enmin Song (1 shared paper)
- Journals
- IEEE Access (3 papers)Future Generation Computer Systems (3 papers)Computer Communications (2 papers)Computers in Biology and Medicine (1 paper)International Journal of Imaging Systems and Technology (1 paper)
- Partner nations
- ChinaSaudi ArabiaIndia
In The Last Decade
Mohd Usama
14 papers receiving 459 citations
Peers
Comparison fields: 5 of 97
- Health Information Management 50
- Artificial Intelligence 249
- Computer Vision and Pattern Recognition 97
- Neurology 38
- Oncology 92
Countries citing papers authored by Mohd Usama
This map shows the geographic impact of Mohd Usama'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 Mohd Usama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohd Usama more than expected).
Fields of papers citing papers by Mohd Usama
This network shows the impact of papers produced by Mohd Usama. 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 Mohd Usama. The network helps show where Mohd Usama may publish in the future.
Co-authors
The 25 scholars most cited alongside Mohd Usama, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 93 | |
| 2 | 2020 | 92 | |
| 3 | 2019 | 84 | |
| 4 | 2018 | 53 | |
| 5 | 2019 | 43 | |
| 6 | 2017 | 31 | |
| 7 | 2019 | 23 | |
| 8 | 2018 | 21 | |
| 9 | 2022 | 19 | |
| 10 | 2021 | 17 | |
| 11 | 2019 | 6 | |
| 12 | 2019 | 5 | |
| 13 | 2019 | 3 | |
| 14 | 2025 | 1 | |
| 15 | 2019 | 1 | |
| 16 | 2019 | 0 |
About Mohd Usama
Mohd Usama is a scholar working on Artificial Intelligence, Health Information Management, Computer Vision and Pattern Recognition, Neurology and Computer Networks and Communications, having authored 16 papers that have together received 492 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (4 papers), Topic Modeling (4 papers), Artificial Intelligence in Healthcare (3 papers), Brain Tumor Detection and Classification (3 papers), AI in cancer detection (3 papers), Machine Learning in Healthcare (3 papers), Cutaneous Melanoma Detection and Management (2 papers) and Text and Document Classification Technologies (2 papers). The work is most often cited by research in Health Information Management (50 citations), Artificial Intelligence (249 citations), Computer Vision and Pattern Recognition (97 citations), Neurology (38 citations) and Oncology (92 citations). Mohd Usama has collaborated with scholars based in China, Saudi Arabia and India. Frequent co-authors include Belal Ahmad, M. Shamim Hossain, Ghulam Muhammad, Saqib Qamar, Parvez Ahmad, Ran Zheng, Hai Jin, Enmin Song, Mubarak Alrashoud and Kai Hwang. Their work appears in journals such as IEEE Access, Future Generation Computer Systems, Computer Communications, Computers in Biology and Medicine and International Journal of Imaging Systems and Technology.
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.