Shadi Basurra
Impact in
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- Artificial Intelligence in Healthcare
- Health Informatics top 10%
Papers in
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- Imbalanced Data Classification Techniques 2
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- Mobile Ad Hoc Networks 3
- IoT and Edge/Fog Computing 3
- Opportunistic and Delay-Tolerant Networks 3
- Co-authors
- Faisal Saeed (10 shared papers)Mohamed Medhat Gaber (8 shared papers)Sultan Noman Qasem (3 shared papers)Abdullah M. Albarrak (1 shared paper)Tawfik Al-Hadhrami (2 shared papers)Marina De Vos (3 shared papers)Simon Armour (3 shared papers)Julián Padget (4 shared papers)
- Journals
- IEEE Access (5 papers)Sensors (3 papers)Scientific Reports (2 papers)Water (2 papers)IEEE Transactions on Consumer Electronics (1 paper)
- Partner nations
- United KingdomSaudi ArabiaJapan
In The Last Decade
Shadi Basurra
29 papers receiving 380 citations
Hit Papers
Peers
Comparison fields: 5 of 97
- Health Information Management 54
- Health Informatics 12
- Computer Networks and Communications 117
- Artificial Intelligence 92
- Computer Vision and Pattern Recognition 46
Countries citing papers authored by Shadi Basurra
This map shows the geographic impact of Shadi Basurra'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 Shadi Basurra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shadi Basurra more than expected).
Fields of papers citing papers by Shadi Basurra
This network shows the impact of papers produced by Shadi Basurra. 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 Shadi Basurra. The network helps show where Shadi Basurra may publish in the future.
Co-authors
The 25 scholars most cited alongside Shadi Basurra, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Machine Learning-Based Predictive Models for Detection of Cardiovascular Diseases Hit paper breakdown → | 2024 | 81 |
| 2 | 2018 | 65 | |
| 3 | 2023 | 63 | |
| 4 | 2014 | 46 | |
| 5 | 2018 | 34 | |
| 6 | 2022 | 14 | |
| 7 | 2024 | 13 | |
| 8 | 2023 | 10 | |
| 9 | 2022 | 10 | |
| 10 | 2023 | 7 | |
| 11 | 2023 | 6 | |
| 12 | 2024 | 5 | |
| 13 | 2024 | 4 | |
| 14 | 2010 | 4 | |
| 15 | 2018 | 4 | |
| 16 | 2022 | 4 | |
| 17 | 2017 | 4 | |
| 18 | 2024 | 3 | |
| 19 | 2023 | 2 | |
| 20 | 2025 | 2 |
About Shadi Basurra
Shadi Basurra is a scholar working on Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems and Computer Vision and Pattern Recognition, having authored 30 papers that have together received 393 indexed citations. Recurring topics across this work include Mobile Ad Hoc Networks (3 papers), IoT and Edge/Fog Computing (3 papers), Opportunistic and Delay-Tolerant Networks (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), COVID-19 diagnosis using AI (2 papers), Artificial Intelligence in Healthcare (2 papers), Water Quality Monitoring Technologies (2 papers) and Imbalanced Data Classification Techniques (2 papers). The work is most often cited by research in Health Information Management (54 citations), Health Informatics (12 citations), Computer Networks and Communications (117 citations), Artificial Intelligence (92 citations) and Computer Vision and Pattern Recognition (46 citations). Shadi Basurra has collaborated with scholars based in United Kingdom, Saudi Arabia and Japan. Frequent co-authors include Faisal Saeed, Mohamed Medhat Gaber, Sultan Noman Qasem, Abdullah M. Albarrak, Tawfik Al-Hadhrami, Marina De Vos, Simon Armour, Julián Padget, Tim Lewis and Yusheng Ji. Their work appears in journals such as IEEE Access, Sensors, Scientific Reports, Water and IEEE Transactions on Consumer Electronics.
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.