Sameem Abdul Kareem
Impact in
- Health Informatics top 5%
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- Digital Imaging for Blood Diseases
Papers in
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- Semantic Web and Ontologies 13
- AI in cancer detection 11
- Neural Networks and Applications 8
- Imbalanced Data Classification Techniques 6
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- Face and Expression Recognition 8
- Co-authors
- Haruna Chiroma (13 shared papers)Tutut Herawan (8 shared papers)Siow‐Wee Chang (5 shared papers)Hany Ariffin (4 shared papers)Rosnah Binti Zain (5 shared papers)Hwa Jen Yap (2 shared papers)Amir Feisal Merican (3 shared papers)Ram Gopal Raj (9 shared papers)
In The Last Decade
Sameem Abdul Kareem
100 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 155
- Health Informatics 32
- Computer Vision and Pattern Recognition 495
- Health Information Management 81
- Artificial Intelligence 595
- Biophysics 102
Countries citing papers authored by Sameem Abdul Kareem
This map shows the geographic impact of Sameem Abdul Kareem'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 Sameem Abdul Kareem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sameem Abdul Kareem more than expected).
Fields of papers citing papers by Sameem Abdul Kareem
This network shows the impact of papers produced by Sameem Abdul Kareem. 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 Sameem Abdul Kareem. The network helps show where Sameem Abdul Kareem may publish in the future.
Co-authors
The 25 scholars most cited alongside Sameem Abdul Kareem, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 161 | |
| 2 | 2015 | 145 | |
| 3 | 2013 | 118 | |
| 4 | 2010 | 113 | |
| 5 | 2010 | 98 | |
| 6 | 2019 | 62 | |
| 7 | 2017 | 61 | |
| 8 | 2017 | 60 | |
| 9 | 2013 | 55 | |
| 10 | 2011 | 54 | |
| 11 | 2012 | 48 | |
| 12 | 2018 | 44 | |
| 13 | 2013 | 43 | |
| 14 | 2015 | 39 | |
| 15 | 2021 | 37 | |
| 16 | 2021 | 35 | |
| 17 | 2022 | 32 | |
| 18 | 2012 | 31 | |
| 19 | 2012 | 30 | |
| 20 | 2016 | 29 |
About Sameem Abdul Kareem
Sameem Abdul Kareem is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications and Management Science and Operations Research, having authored 103 papers that have together received 1.8k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (13 papers), AI in cancer detection (11 papers), Advanced Database Systems and Queries (10 papers), Face and Expression Recognition (8 papers), Service-Oriented Architecture and Web Services (8 papers), Neural Networks and Applications (8 papers), Stock Market Forecasting Methods (7 papers) and Imbalanced Data Classification Techniques (6 papers). The work is most often cited by research in Health Informatics (32 citations), Computer Vision and Pattern Recognition (495 citations), Health Information Management (81 citations), Artificial Intelligence (595 citations) and Biophysics (102 citations). Sameem Abdul Kareem has collaborated with scholars based in Malaysia, Pakistan and Nigeria. Frequent co-authors include Haruna Chiroma, Tutut Herawan, Siow‐Wee Chang, Hany Ariffin, Rosnah Binti Zain, Hwa Jen Yap, Amir Feisal Merican, Ram Gopal Raj, Kien‐Thai Yong and Maizatul Akmar Ismail. Their work appears in journals such as IEEE Access, Computers in Biology and Medicine, Artificial intelligence for engineering design analysis and manufacturing, Applied Soft Computing and Journal of the Association for Information Science 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.