Euijoon Ahn
Impact in
- Oncology top 5%
- Cutaneous Melanoma Detection and Management
- Artificial Intelligence top 2%
- AI in cancer detection
Papers in
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- AI in cancer detection 12
- Domain Adaptation and Few-Shot Learning 4
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- Radiomics and Machine Learning in Medical Imaging 8
- Co-authors
- Jinman Kim (26 shared papers)Dagan Feng (18 shared papers)Michael Fulham (11 shared papers)Lei Bi (9 shared papers)Ashnil Kumar (7 shared papers)Changyang Li (3 shared papers)Lin Schwarzkopf (2 shared papers)Zhengmin Kong (3 shared papers)
In The Last Decade
Euijoon Ahn
32 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 102
- Oncology 641
- Artificial Intelligence 645
- Computer Vision and Pattern Recognition 280
- Biophysics 57
- Radiology, Nuclear Medicine and Imaging 203
Countries citing papers authored by Euijoon Ahn
This map shows the geographic impact of Euijoon Ahn'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 Euijoon Ahn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Euijoon Ahn more than expected).
Fields of papers citing papers by Euijoon Ahn
This network shows the impact of papers produced by Euijoon Ahn. 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 Euijoon Ahn. The network helps show where Euijoon Ahn may publish in the future.
Co-authors
The 25 scholars most cited alongside Euijoon Ahn, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 263 | |
| 2 | 2018 | 164 | |
| 3 | 2017 | 130 | |
| 4 | 2016 | 71 | |
| 5 | 2016 | 64 | |
| 6 | 2015 | 52 | |
| 7 | 2020 | 43 | |
| 8 | 2022 | 36 | |
| 9 | 2019 | 33 | |
| 10 | 2019 | 33 | |
| 11 | 2016 | 32 | |
| 12 | 2022 | 31 | |
| 13 | 2023 | 28 | |
| 14 | 2021 | 24 | |
| 15 | 2024 | 23 | |
| 16 | 2017 | 23 | |
| 17 | 2020 | 18 | |
| 18 | 2024 | 15 | |
| 19 | 2021 | 15 | |
| 20 | 2025 | 6 |
About Euijoon Ahn
Euijoon Ahn is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Oncology and Biomedical Engineering, having authored 36 papers that have together received 1.1k indexed citations. Recurring topics across this work include AI in cancer detection (12 papers), Cutaneous Melanoma Detection and Management (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Domain Adaptation and Few-Shot Learning (4 papers), Medical Image Segmentation Techniques (3 papers), Cell Image Analysis Techniques (3 papers), Advanced Neural Network Applications (3 papers) and Image and Signal Denoising Methods (3 papers). The work is most often cited by research in Oncology (641 citations), Artificial Intelligence (645 citations), Computer Vision and Pattern Recognition (280 citations), Biophysics (57 citations) and Radiology, Nuclear Medicine and Imaging (203 citations). Euijoon Ahn has collaborated with scholars based in Australia, China and Germany. Frequent co-authors include Jinman Kim, Dagan Feng, Michael Fulham, Lei Bi, Ashnil Kumar, Changyang Li, Lin Schwarzkopf, Zhengmin Kong, Tao Huang and Ickjai Lee. Their work appears in journals such as Pattern Recognition, IEEE Journal of Biomedical and Health Informatics, Ecological Informatics, Expert Systems with Applications and IEEE Transactions on Medical Imaging.
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.