Aurélie Kas
Impact in
- Neurology top 2%
- Autoimmune Neurological Disorders and Treatments
- Long-Term Effects of COVID-19
- Peripheral Neuropathies and Disorders
- Cognitive Neuroscience top 5%
- Functional Brain Connectivity Studies
Papers in
- Co-authors
- Marie‐Odile Habert (22 shared papers)Antoine Verger (9 shared papers)Éric Guedj (9 shared papers)Vincent Navarro (5 shared papers)Bruno Dubois (6 shared papers)L. Chami (3 shared papers)Marie Sarazin (6 shared papers)Isabelle Arnulf (2 shared papers)
- Journals
- European Journal of Nuclear Medicine and Molecular Imaging (5 papers)Neurology (4 papers)European Journal of Neurology (3 papers)Brain (3 papers)European Radiology (2 papers)
- Partner nations
- FranceUnited StatesItaly
In The Last Decade
Aurélie Kas
69 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 83
- Neurology 515
- Cognitive Neuroscience 253
- Neurology 103
- Genetics 112
- Psychiatry and Mental health 152
Countries citing papers authored by Aurélie Kas
This map shows the geographic impact of Aurélie Kas'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 Aurélie Kas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aurélie Kas more than expected).
Fields of papers citing papers by Aurélie Kas
This network shows the impact of papers produced by Aurélie Kas. 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 Aurélie Kas. The network helps show where Aurélie Kas may publish in the future.
Co-authors
The 25 scholars most cited alongside Aurélie Kas, 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 74 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 144 | |
| 2 | 2020 | 109 | |
| 3 | 2010 | 91 | |
| 4 | 2021 | 73 | |
| 5 | 2014 | 54 | |
| 6 | 2019 | 53 | |
| 7 | 2016 | 45 | |
| 8 | 2021 | 45 | |
| 9 | 2009 | 43 | |
| 10 | 2022 | 41 | |
| 11 | 2009 | 39 | |
| 12 | 2022 | 39 | |
| 13 | 2008 | 35 | |
| 14 | 2017 | 33 | |
| 15 | 2016 | 32 | |
| 16 | 2020 | 31 | |
| 17 | 2021 | 25 | |
| 18 | 2019 | 23 | |
| 19 | 2012 | 19 | |
| 20 | 2021 | 17 |
About Aurélie Kas
Aurélie Kas is a scholar working on Neurology, Genetics, Radiology, Nuclear Medicine and Imaging, Cellular and Molecular Neuroscience and Cognitive Neuroscience, having authored 74 papers that have together received 1.3k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (15 papers), CNS Lymphoma Diagnosis and Treatment (9 papers), Medical Imaging Techniques and Applications (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Autoimmune Neurological Disorders and Treatments (6 papers), Advanced MRI Techniques and Applications (6 papers), Long-Term Effects of COVID-19 (6 papers) and Lymphoma Diagnosis and Treatment (5 papers). The work is most often cited by research in Neurology (515 citations), Cognitive Neuroscience (253 citations), Neurology (103 citations), Genetics (112 citations) and Psychiatry and Mental health (152 citations). Aurélie Kas has collaborated with scholars based in France, United States and Italy. Frequent co-authors include Marie‐Odile Habert, Antoine Verger, Éric Guedj, Vincent Navarro, Bruno Dubois, L. Chami, Marie Sarazin, Isabelle Arnulf, Sophie Lavault and Jean‐Yves Delattre. Their work appears in journals such as European Journal of Nuclear Medicine and Molecular Imaging, Neurology, European Journal of Neurology, Brain and European Radiology.
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.