Tabea Kossen
Impact in
- Health Informatics top 10%
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- Brain Tumor Detection and Classification
Papers in
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- Acute Ischemic Stroke Management 5
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- Generative Adversarial Networks and Image Synthesis 4
- Co-authors
- Vince I. Madai (10 shared papers)Dietmar Frey (9 shared papers)Jan Sobesky (8 shared papers)Michelle Livne (4 shared papers)Kristian Hildebrand (5 shared papers)Jana Rieger (1 shared paper)Abdel Aziz Taha (1 shared paper)Orhun Utku Aydin (3 shared papers)
- Journals
- Frontiers in Neurology (2 papers)Neurosurgical Review (1 paper)Stroke (1 paper)Computers in Biology and Medicine (1 paper)Frontiers in Neuroscience (1 paper)
- Partner nations
- GermanyUnited KingdomAustria
In The Last Decade
Tabea Kossen
13 papers receiving 347 citations
Peers
Comparison fields: 5 of 63
- Health Informatics 15
- Neurology 58
- Computer Vision and Pattern Recognition 130
- Radiology, Nuclear Medicine and Imaging 108
- Biophysics 12
Countries citing papers authored by Tabea Kossen
This map shows the geographic impact of Tabea Kossen'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 Tabea Kossen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tabea Kossen more than expected).
Fields of papers citing papers by Tabea Kossen
This network shows the impact of papers produced by Tabea Kossen. 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 Tabea Kossen. The network helps show where Tabea Kossen may publish in the future.
Co-authors
The 25 scholars most cited alongside Tabea Kossen, 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 | 2019 | 183 | |
| 2 | 2021 | 51 | |
| 3 | 2024 | 33 | |
| 4 | 2022 | 32 | |
| 5 | 2021 | 11 | |
| 6 | 2023 | 8 | |
| 7 | 2022 | 8 | |
| 8 | 2022 | 7 | |
| 9 | 2023 | 6 | |
| 10 | 2017 | 5 | |
| 11 | 2021 | 3 | |
| 12 | 2024 | 2 | |
| 13 | 2023 | 1 |
About Tabea Kossen
Tabea Kossen is a scholar working on Epidemiology, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 13 papers that have together received 350 indexed citations. Recurring topics across this work include Acute Ischemic Stroke Management (5 papers), Generative Adversarial Networks and Image Synthesis (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Cerebrovascular and Carotid Artery Diseases (3 papers), Traumatic Brain Injury and Neurovascular Disturbances (2 papers), Intracranial Aneurysms: Treatment and Complications (2 papers), COVID-19 diagnosis using AI (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Informatics (15 citations), Neurology (58 citations), Computer Vision and Pattern Recognition (130 citations), Radiology, Nuclear Medicine and Imaging (108 citations) and Biophysics (12 citations). Tabea Kossen has collaborated with scholars based in Germany, United Kingdom and Austria. Frequent co-authors include Vince I. Madai, Dietmar Frey, Jan Sobesky, Michelle Livne, Kristian Hildebrand, Jana Rieger, Abdel Aziz Taha, Orhun Utku Aydin, Ela M. Akay and John D. Kelleher. Their work appears in journals such as Frontiers in Neurology, Neurosurgical Review, Stroke, Computers in Biology and Medicine and Frontiers in Neuroscience.
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.