Oğuz Ata
Impact in
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- Artificial Intelligence in Healthcare
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- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
Papers in
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- Imbalanced Data Classification Techniques 5
- Anomaly Detection Techniques and Applications 2
- Co-authors
- Dilek Turgut‐Balik (4 shared papers)Mazen Almehmadi (2 shared papers)Mohammad N. Alomary (2 shared papers)Mohammad Azam Ansari (2 shared papers)Özal Mutlu (2 shared papers)Saad Alghamdi (1 shared paper)Omar Hussein Salman (3 shared papers)Aydoğan Özdemir (1 shared paper)
- Journals
- PeerJ Computer Science (2 papers)Electronics (2 papers)Applied Sciences (1 paper)International Journal of Medical Informatics (1 paper)Journal of Biomolecular Structure and Dynamics (1 paper)
- Partner nations
- TürkiyeIraqSaudi Arabia
In The Last Decade
Oğuz Ata
35 papers receiving 267 citations
Peers
Comparison fields: 5 of 83
- Health Information Management 32
- Infectious Diseases 71
- Health Informatics 5
- Medical Laboratory Technology 3
- Artificial Intelligence 60
Countries citing papers authored by Oğuz Ata
This map shows the geographic impact of Oğuz Ata'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 Oğuz Ata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oğuz Ata more than expected).
Fields of papers citing papers by Oğuz Ata
This network shows the impact of papers produced by Oğuz Ata. 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 Oğuz Ata. The network helps show where Oğuz Ata may publish in the future.
Co-authors
The 14 scholars most cited alongside Oğuz Ata, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 45 | |
| 2 | 2020 | 29 | |
| 3 | 2021 | 27 | |
| 4 | 2022 | 25 | |
| 5 | 2020 | 22 | |
| 6 | 2021 | 14 | |
| 7 | 2022 | 11 | |
| 8 | 2020 | 11 | |
| 9 | 2022 | 10 | |
| 10 | 2020 | 10 | |
| 11 | 2023 | 9 | |
| 12 | 2025 | 9 | |
| 13 | 2022 | 8 | |
| 14 | 2021 | 5 | |
| 15 | 2024 | 4 | |
| 16 | 2023 | 4 | |
| 17 | 2017 | 4 | |
| 18 | 2024 | 3 | |
| 19 | 2021 | 3 | |
| 20 | 2024 | 2 |
About Oğuz Ata
Oğuz Ata is a scholar working on Artificial Intelligence, Computer Networks and Communications, Health Information Management, Radiology, Nuclear Medicine and Imaging and Infectious Diseases, having authored 37 papers that have together received 275 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (5 papers), Imbalanced Data Classification Techniques (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers), COVID-19 diagnosis using AI (3 papers), Vehicle License Plate Recognition (2 papers), Blockchain Technology Applications and Security (2 papers), Robotic Path Planning Algorithms (2 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Health Information Management (32 citations), Infectious Diseases (71 citations), Health Informatics (5 citations), Medical Laboratory Technology (3 citations) and Artificial Intelligence (60 citations). Oğuz Ata has collaborated with scholars based in Türkiye, Iraq and Saudi Arabia. Frequent co-authors include Dilek Turgut‐Balik, Mazen Almehmadi, Mohammad N. Alomary, Mohammad Azam Ansari, Özal Mutlu, Saad Alghamdi, Omar Hussein Salman, Aydoğan Özdemir, Oğuz Bayat and Abdullahi Abdu İbrahim. Their work appears in journals such as PeerJ Computer Science, Electronics, Applied Sciences, International Journal of Medical Informatics and Journal of Biomolecular Structure and Dynamics.
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.