Dheeb Albashish
Impact in
- Artificial Intelligence top 10%
- AI in cancer detection
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- AI in cancer detection 12
- Imbalanced Data Classification Techniques 2
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- Digital Imaging for Blood Diseases 2
- Face and Expression Recognition 2
- Co-authors
- Azizi Abdullah (8 shared papers)Shahnorbanun Sahran (9 shared papers)Mohammad Hashem Ryalat (2 shared papers)Rizik Al-Sayyed (1 shared paper)Ravie Chandren Muniyandi (1 shared paper)Opeyemi Lateef Usman (1 shared paper)Afzan Adam (3 shared papers)Mohammed Alweshah (2 shared papers)
- Journals
- PeerJ Computer Science (2 papers)The Computer Journal (1 paper)Artificial Intelligence in Medicine (1 paper)Neural Computing and Applications (1 paper)Journal of Information and Communication Technology (2 papers)
- Partner nations
- JordanMalaysiaSaudi Arabia
In The Last Decade
Dheeb Albashish
14 papers receiving 270 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 171
- Radiology, Nuclear Medicine and Imaging 106
- Health Information Management 20
- Neurology 26
- Computer Vision and Pattern Recognition 62
Countries citing papers authored by Dheeb Albashish
This map shows the geographic impact of Dheeb Albashish'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 Dheeb Albashish with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dheeb Albashish more than expected).
Fields of papers citing papers by Dheeb Albashish
This network shows the impact of papers produced by Dheeb Albashish. 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 Dheeb Albashish. The network helps show where Dheeb Albashish may publish in the future.
Co-authors
The 14 scholars most cited alongside Dheeb Albashish, 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 | 2021 | 82 | |
| 2 | 2018 | 64 | |
| 3 | 2021 | 38 | |
| 4 | 2022 | 26 | |
| 5 | 2022 | 18 | |
| 6 | 2016 | 10 | |
| 7 | 2018 | 10 | |
| 8 | 2015 | 9 | |
| 9 | 2018 | 7 | |
| 10 | 2018 | 6 | |
| 11 | 2024 | 5 | |
| 12 | 2017 | 2 | |
| 13 | 2024 | 1 | |
| 14 | 2021 | 1 |
About Dheeb Albashish
Dheeb Albashish is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 14 papers that have together received 279 indexed citations. Recurring topics across this work include AI in cancer detection (12 papers), Medical Imaging and Analysis (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Gene expression and cancer classification (3 papers), Imbalanced Data Classification Techniques (2 papers), Digital Imaging for Blood Diseases (2 papers), Face and Expression Recognition (2 papers) and Artificial Intelligence in Healthcare (1 paper). The work is most often cited by research in Artificial Intelligence (171 citations), Radiology, Nuclear Medicine and Imaging (106 citations), Health Information Management (20 citations), Neurology (26 citations) and Computer Vision and Pattern Recognition (62 citations). Dheeb Albashish has collaborated with scholars based in Jordan, Malaysia and Saudi Arabia. Frequent co-authors include Azizi Abdullah, Shahnorbanun Sahran, Mohammad Hashem Ryalat, Rizik Al-Sayyed, Ravie Chandren Muniyandi, Opeyemi Lateef Usman, Afzan Adam, Mohammed Alweshah, Siti Norul Huda Sheikh Abdullah and Shidrokh Goudarzi. Their work appears in journals such as PeerJ Computer Science, The Computer Journal, Artificial Intelligence in Medicine, Neural Computing and Applications and Journal of Information and Communication 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.