Anouk Stein
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
- Radiology practices and education
Papers in
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- Radiomics and Machine Learning in Medical Imaging 4
- COVID-19 diagnosis using AI 3
- Radiology practices and education 2
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- Ultrasound in Clinical Applications 2
- Co-authors
- George Shih (3 shared papers)Carol C. Wu (2 shared papers)Ritu R. Gill (2 shared papers)Palmi Shah (2 shared papers)Veronica A. Arteaga (2 shared papers)Archana T. Laroia (2 shared papers)Jean J. Jeudy (2 shared papers)Stephen Hobbs (2 shared papers)
- Journals
- Radiology Artificial Intelligence (4 papers)Journal of Imaging Informatics in Medicine (2 papers)International Journal of Radiation Oncology*Biology*Physics (1 paper)Transplantation and Cellular Therapy (1 paper)Surgical Clinics of North America (1 paper)
- Partner nations
- United StatesCanadaSpain
In The Last Decade
Anouk Stein
12 papers receiving 654 citations
Peers
Comparison fields: 5 of 43
- Health Informatics 119
- Radiology, Nuclear Medicine and Imaging 407
- Internal Medicine 38
- Artificial Intelligence 241
- Neurology 70
Countries citing papers authored by Anouk Stein
This map shows the geographic impact of Anouk Stein'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 Anouk Stein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anouk Stein more than expected).
Fields of papers citing papers by Anouk Stein
This network shows the impact of papers produced by Anouk Stein. 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 Anouk Stein. The network helps show where Anouk Stein may publish in the future.
Co-authors
The 25 scholars most cited alongside Anouk Stein, 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 | 229 | |
| 2 | 2020 | 153 | |
| 3 | 2021 | 110 | |
| 4 | 2021 | 66 | |
| 5 | 2019 | 43 | |
| 6 | 2020 | 38 | |
| 7 | 2001 | 13 | |
| 8 | 2004 | 10 | |
| 9 | 2022 | 8 | |
| 10 | 2006 | 3 | |
| 11 | 2024 | 2 | |
| 12 | 1998 | 2 |
About Anouk Stein
Anouk Stein is a scholar working on Radiology, Nuclear Medicine and Imaging, Critical Care and Intensive Care Medicine, Oncology, Neurology and Surgery, having authored 12 papers that have together received 677 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), COVID-19 diagnosis using AI (3 papers), Intracerebral and Subarachnoid Hemorrhage Research (2 papers), Radiology practices and education (2 papers), Ultrasound in Clinical Applications (2 papers), Pancreatic and Hepatic Oncology Research (2 papers), Pancreatitis Pathology and Treatment (2 papers) and Lung Cancer Diagnosis and Treatment (2 papers). The work is most often cited by research in Health Informatics (119 citations), Radiology, Nuclear Medicine and Imaging (407 citations), Internal Medicine (38 citations), Artificial Intelligence (241 citations) and Neurology (70 citations). Anouk Stein has collaborated with scholars based in United States, Canada and Spain. Frequent co-authors include George Shih, Carol C. Wu, Ritu R. Gill, Palmi Shah, Veronica A. Arteaga, Archana T. Laroia, Jean J. Jeudy, Stephen Hobbs, Maya Galperin-Aizenberg and Kavitha Yaddanapudi. Their work appears in journals such as Radiology Artificial Intelligence, Journal of Imaging Informatics in Medicine, International Journal of Radiation Oncology*Biology*Physics, Transplantation and Cellular Therapy and Surgical Clinics of North America.
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.