Georg Wölflein
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Cell Image Analysis Techniques
Papers in
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- AI in cancer detection 7
- Artificial Intelligence in Games 1
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- Radiomics and Machine Learning in Medical Imaging 6
- Co-authors
- Daniel Truhn (7 shared papers)Jakob Nikolas Kather (8 shared papers)Isabella C. Wiest (3 shared papers)Dyke Ferber (5 shared papers)Omar S. M. El Nahhas (5 shared papers)Dirk Jäger (2 shared papers)Marta Ligero (4 shared papers)Narmin Ghaffari Laleh (1 shared paper)
- Journals
- Nature Protocols (1 paper)Nature Cancer (1 paper)Cancers (1 paper)Nature Communications (1 paper)Lecture notes in computer science (2 papers)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Georg Wölflein
9 papers receiving 210 citations
Georg Wölflein's Hit Papers
Peers
Comparison fields: 5 of 43
- Health Informatics 50
- Biophysics 16
- Artificial Intelligence 75
- Radiology, Nuclear Medicine and Imaging 41
- Health Information Management 7
Countries citing papers authored by Georg Wölflein
This map shows the geographic impact of Georg Wölflein'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 Georg Wölflein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Georg Wölflein more than expected).
Fields of papers citing papers by Georg Wölflein
This network shows the impact of papers produced by Georg Wölflein. 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 Georg Wölflein. The network helps show where Georg Wölflein may publish in the future.
Co-authors
The 25 scholars most cited alongside Georg Wölflein, 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 | In-context learning enables multimodal large language models to classify cancer pathology images Hit paper breakdown → | 2024 | 62 |
| 2 | 2024 | 51 | |
| 3 | Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology Hit paper breakdown → | 2025 | 41 |
| 4 | 2024 | 38 | |
| 5 | 2023 | 8 | |
| 6 | 2022 | 7 | |
| 7 | 2025 | 3 | |
| 8 | 2021 | 1 | |
| 9 | 2023 | 1 | |
| 10 | 2025 | 0 | |
| 11 | 2024 | 0 | |
| 12 | 2025 | 0 |
About Georg Wölflein
Georg Wölflein is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Cancer Research and Pulmonary and Respiratory Medicine, having authored 12 papers that have together received 212 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Cancer Genomics and Diagnostics (3 papers), Digital Imaging for Blood Diseases (3 papers), Renal cell carcinoma treatment (2 papers), Cell Image Analysis Techniques (2 papers), Artificial Intelligence in Games (1 paper) and Pancreatic and Hepatic Oncology Research (1 paper). The work is most often cited by research in Health Informatics (50 citations), Biophysics (16 citations), Artificial Intelligence (75 citations), Radiology, Nuclear Medicine and Imaging (41 citations) and Health Information Management (7 citations). Georg Wölflein has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Daniel Truhn, Jakob Nikolas Kather, Isabella C. Wiest, Dyke Ferber, Omar S. M. El Nahhas, Dirk Jäger, Marta Ligero, Narmin Ghaffari Laleh, Sebastian Foersch and Gustav Müller‐Franzes. Their work appears in journals such as Nature Protocols, Nature Cancer, Cancers, Nature Communications and Lecture notes in computer science.
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.