Anouk Stein
Impact in
- Health Informatics top 5%
- 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
-
- Radiomics and Machine Learning in Medical Imaging 3
- COVID-19 diagnosis using AI 3
- Radiology practices and education 2
- Surgery 4
- Pancreatitis Pathology and Treatment 2
- Co-authors
- George Shih (4 shared papers)Carol C. Wu (2 shared papers)Jean Jeudy (2 shared papers)Dharshan Vummidi (2 shared papers)Ritu R. Gill (2 shared papers)Maya Galperin-Aizenberg (2 shared papers)Archana Laroia (2 shared papers)Stephen Hobbs (2 shared papers)
- Journals
- Journal of Digital Imaging (2 papers)Radiology Artificial Intelligence (1 paper)Gastroenterology (1 paper)Surgical Clinics of North America (1 paper)International Journal of Radiation Oncology*Biology*Physics (1 paper)
- Partner nations
- United StatesCanadaAustralia
In The Last Decade
Anouk Stein
8 papers receiving 293 citations
Peers
Comparison fields: 5 of 36
- Health Informatics 46
- Radiology, Nuclear Medicine and Imaging 201
- Artificial Intelligence 127
- Computer Vision and Pattern Recognition 64
- Transplantation 5
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 | 215 | |
| 2 | 2019 | 40 | |
| 3 | 2021 | 14 | |
| 4 | 2001 | 12 | |
| 5 | 2004 | 10 | |
| 6 | 2022 | 7 | |
| 7 | 2006 | 3 | |
| 8 | 1998 | 2 | |
| 9 | 2024 | 0 |
About Anouk Stein
Anouk Stein is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery, Oncology, Pulmonary and Respiratory Medicine and Otorhinolaryngology, having authored 9 papers that have together received 303 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), COVID-19 diagnosis using AI (3 papers), Pancreatic and Hepatic Oncology Research (2 papers), Pancreatitis Pathology and Treatment (2 papers), Radiology practices and education (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Advanced Radiotherapy Techniques (1 paper) and Head and Neck Cancer Studies (1 paper). The work is most often cited by research in Health Informatics (46 citations), Radiology, Nuclear Medicine and Imaging (201 citations), Artificial Intelligence (127 citations), Computer Vision and Pattern Recognition (64 citations) and Transplantation (5 citations). Anouk Stein has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include George Shih, Carol C. Wu, Jean Jeudy, Dharshan Vummidi, Ritu R. Gill, Maya Galperin-Aizenberg, Archana Laroia, Stephen Hobbs, Kavitha Yaddanapudi and Palmi Shah. Their work appears in journals such as Journal of Digital Imaging, Radiology Artificial Intelligence, Gastroenterology, Surgical Clinics of North America and International Journal of Radiation Oncology*Biology*Physics.
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.