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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- Radiomics and Machine Learning in Medical Imaging 7
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- AI in cancer detection 11
- Domain Adaptation and Few-Shot Learning 3
- Co-authors
- Dagan Feng (17 shared papers)Michael Fulham (11 shared papers)Lei Bi (9 shared papers)Ashnil Kumar (7 shared papers)Jinman Kim (19 shared papers)Jinman Kim (6 shared papers)Changyang Li (3 shared papers)Ickjai Lee (2 shared papers)
In The Last Decade
Euijoon Ahn
26 papers receiving 937 citations
Peers
Comparison fields: 5 of 102
- Oncology 572
- Artificial Intelligence 571
- Computer Vision and Pattern Recognition 227
- Health Informatics 12
- Biophysics 47
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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 234 | |
| 2 | 2018 | 151 | |
| 3 | 2017 | 110 | |
| 4 | 2016 | 62 | |
| 5 | 2016 | 58 | |
| 6 | 2015 | 43 | |
| 7 | 2020 | 38 | |
| 8 | 2022 | 32 | |
| 9 | 2019 | 30 | |
| 10 | 2016 | 28 | |
| 11 | 2019 | 27 | |
| 12 | 2022 | 25 | |
| 13 | 2023 | 23 | |
| 14 | 2024 | 20 | |
| 15 | 2017 | 18 | |
| 16 | 2020 | 16 | |
| 17 | 2021 | 13 | |
| 18 | 2024 | 10 | |
| 19 | 2018 | 6 | |
| 20 | 2023 | 4 |
About Euijoon Ahn
Euijoon Ahn is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computer Vision and Pattern Recognition, Oncology and Epidemiology, having authored 31 papers that have together received 957 indexed citations. Recurring topics across this work include AI in cancer detection (11 papers), Cutaneous Melanoma Detection and Management (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Cell Image Analysis Techniques (3 papers), Industrial Vision Systems and Defect Detection (3 papers), Domain Adaptation and Few-Shot Learning (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 (572 citations), Artificial Intelligence (571 citations), Computer Vision and Pattern Recognition (227 citations), Health Informatics (12 citations) and Biophysics (47 citations). Euijoon Ahn has collaborated with scholars based in Australia, China and Germany. Frequent co-authors include Dagan Feng, Michael Fulham, Lei Bi, Ashnil Kumar, Jinman Kim, Jinman Kim, Changyang Li, Ickjai Lee, Lin Schwarzkopf and Yiyuan Cao. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, Pattern Recognition, BMJ Open, Electronics and Clinical 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.