Ural Koç
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
-
- Radiomics and Machine Learning in Medical Imaging
- Radiology practices and education
- COVID-19 diagnosis using AI
Papers in
- Surgery 8
- Pancreatitis Pathology and Treatment 2
-
- Vascular Procedures and Complications 3
- Sarcoma Diagnosis and Treatment 1
- Co-authors
- William Parker (2 shared papers)Martin Kočí (2 shared papers)Marc Zins (2 shared papers)Jie Wu (2 shared papers)Satyam Veean (2 shared papers)Dominik Fleischmann (2 shared papers)Tim Leiner (2 shared papers)Daniel Pinto dos Santos (2 shared papers)
- Journals
- European Radiology (2 papers)Clinical Neurology and Neurosurgery (1 paper)International Journal of Radiation Biology (1 paper)Biomarkers in Medicine (1 paper)Child s Nervous System (1 paper)
- Partner nations
- TürkiyeUnited StatesBelgium
In The Last Decade
Ural Koç
25 papers receiving 356 citations
Peers
Comparison fields: 5 of 61
- Health Informatics 184
- Radiology, Nuclear Medicine and Imaging 88
- Family Practice 4
- General Dentistry 2
- Neurology 10
Countries citing papers authored by Ural Koç
This map shows the geographic impact of Ural Koç'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 Ural Koç with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ural Koç more than expected).
Fields of papers citing papers by Ural Koç
This network shows the impact of papers produced by Ural Koç. 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 Ural Koç. The network helps show where Ural Koç may publish in the future.
Co-authors
The 25 scholars most cited alongside Ural Koç, 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 | 2021 | 151 | |
| 2 | 2021 | 97 | |
| 3 | 2020 | 16 | |
| 4 | 2022 | 15 | |
| 5 | 2017 | 13 | |
| 6 | 2021 | 9 | |
| 7 | 2020 | 8 | |
| 8 | 2018 | 8 | |
| 9 | 2021 | 7 | |
| 10 | 2020 | 7 | |
| 11 | 2020 | 6 | |
| 12 | 2019 | 5 | |
| 13 | 2022 | 3 | |
| 14 | 2025 | 2 | |
| 15 | 2018 | 2 | |
| 16 | 2016 | 2 | |
| 17 | 2020 | 2 | |
| 18 | 2025 | 2 | |
| 19 | 2017 | 1 | |
| 20 | 2018 | 1 |
About Ural Koç
Ural Koç is a scholar working on Surgery, Pulmonary and Respiratory Medicine, Health Informatics, Cardiology and Cardiovascular Medicine and Artificial Intelligence, having authored 30 papers that have together received 362 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (6 papers), Vascular Procedures and Complications (3 papers), Machine Learning in Healthcare (2 papers), Liver Disease Diagnosis and Treatment (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Pancreatitis Pathology and Treatment (2 papers), Topic Modeling (2 papers) and Sarcoma Diagnosis and Treatment (1 paper). The work is most often cited by research in Health Informatics (184 citations), Radiology, Nuclear Medicine and Imaging (88 citations), Family Practice (4 citations), General Dentistry (2 citations) and Neurology (10 citations). Ural Koç has collaborated with scholars based in Türkiye, United States and Belgium. Frequent co-authors include William Parker, Martin Kočí, Marc Zins, Jie Wu, Satyam Veean, Dominik Fleischmann, Tim Leiner, Daniel Pinto dos Santos, Merel Huisman and Martin J. Willemink. Their work appears in journals such as European Radiology, Clinical Neurology and Neurosurgery, International Journal of Radiation Biology, Biomarkers in Medicine and Child s Nervous System.
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.