Mubarak Albathan
Impact in
- Artificial Intelligence top 10%
- Text and Document Classification Technologies
- AI in cancer detection
- Topic Modeling
- Advanced Text Analysis Techniques
Papers in
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- Text and Document Classification Technologies 3
- Advanced Text Analysis Techniques 3
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- Data Mining Algorithms and Applications 3
- Web Data Mining and Analysis 2
- Co-authors
- Ayyaz Hussain (8 shared papers)Yuefeng Li (5 shared papers)Qaisar Abbas (7 shared papers)Sohail Jabbar (3 shared papers)Abdulmohsen Algarni (2 shared papers)Moch Arif Bijaksana (1 shared paper)Yan Shen (1 shared paper)Tahira Nazir (1 shared paper)
- Journals
- Granular Computing (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)Sensors (1 paper)Renal Failure (1 paper)Diagnostics (3 papers)
- Partner nations
- Saudi ArabiaPakistanAustralia
In The Last Decade
Mubarak Albathan
14 papers receiving 214 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 111
- Health Informatics 4
- Radiology, Nuclear Medicine and Imaging 61
- Ophthalmology 18
- Information Systems 39
Countries citing papers authored by Mubarak Albathan
This map shows the geographic impact of Mubarak Albathan'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 Mubarak Albathan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mubarak Albathan more than expected).
Fields of papers citing papers by Mubarak Albathan
This network shows the impact of papers produced by Mubarak Albathan. 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 Mubarak Albathan. The network helps show where Mubarak Albathan may publish in the future.
Co-authors
The 23 scholars most cited alongside Mubarak Albathan, 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 | 2014 | 47 | |
| 2 | 2023 | 46 | |
| 3 | 2023 | 29 | |
| 4 | 2023 | 20 | |
| 5 | 2015 | 18 | |
| 6 | 2023 | 14 | |
| 7 | 2023 | 13 | |
| 8 | 2023 | 10 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 9 | |
| 11 | 2014 | 4 | |
| 12 | 2023 | 2 | |
| 13 | 2024 | 2 | |
| 14 | 2012 | 2 | |
| 15 | 2026 | 0 |
About Mubarak Albathan
Mubarak Albathan is a scholar working on Artificial Intelligence, Information Systems, Radiology, Nuclear Medicine and Imaging, Computer Networks and Communications and Ophthalmology, having authored 15 papers that have together received 226 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (3 papers), Data Mining Algorithms and Applications (3 papers), Advanced Text Analysis Techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Retinal Imaging and Analysis (2 papers), Retinal Diseases and Treatments (2 papers), Retinal and Optic Conditions (2 papers) and Web Data Mining and Analysis (2 papers). The work is most often cited by research in Artificial Intelligence (111 citations), Health Informatics (4 citations), Radiology, Nuclear Medicine and Imaging (61 citations), Ophthalmology (18 citations) and Information Systems (39 citations). Mubarak Albathan has collaborated with scholars based in Saudi Arabia, Pakistan and Australia. Frequent co-authors include Ayyaz Hussain, Yuefeng Li, Qaisar Abbas, Sohail Jabbar, Abdulmohsen Algarni, Moch Arif Bijaksana, Yan Shen, Tahira Nazir, Muhammad Munwar Iqbal and Kashif Shaheed. Their work appears in journals such as Granular Computing, IEEE Transactions on Knowledge and Data Engineering, Sensors, Renal Failure and Diagnostics.
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.