Yan‐Wei Lee
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Ultrasound Imaging and Elastography
- Health Informatics top 10%
Papers in
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- Radiomics and Machine Learning in Medical Imaging 7
- Ultrasound Imaging and Elastography 2
- COVID-19 diagnosis using AI 1
- Medical Imaging Techniques and Applications 1
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- AI in cancer detection 8
- Co-authors
- Ruey‐Feng Chang (10 shared papers)Chiun‐Sheng Huang (5 shared papers)Woo Kyung Moon (2 shared papers)Su Hyun Lee (1 shared paper)Yao‐Sian Huang (1 shared paper)Chih‐Yen Tu (1 shared paper)Min Sun Bae (2 shared papers)Chia‐Hung Chen (1 shared paper)
- Journals
- Computer Methods and Programs in Biomedicine (3 papers)Computers in Biology and Medicine (1 paper)Artificial Intelligence in Medicine (1 paper)Medical Physics (1 paper)Biomedical Signal Processing and Control (1 paper)
- Partner nations
- TaiwanSouth KoreaUnited States
In The Last Decade
Yan‐Wei Lee
12 papers receiving 425 citations
Yan‐Wei Lee's Hit Papers
Peers
Comparison fields: 5 of 56
- Radiology, Nuclear Medicine and Imaging 304
- Health Informatics 16
- Artificial Intelligence 329
- Neurology 60
- Media Technology 34
Countries citing papers authored by Yan‐Wei Lee
This map shows the geographic impact of Yan‐Wei Lee'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 Yan‐Wei Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan‐Wei Lee more than expected).
Fields of papers citing papers by Yan‐Wei Lee
This network shows the impact of papers produced by Yan‐Wei Lee. 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 Yan‐Wei Lee. The network helps show where Yan‐Wei Lee may publish in the future.
Co-authors
The 25 scholars most cited alongside Yan‐Wei Lee, 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 | Computer‐aided diagnosis of breast ultrasound images using ensemble learning from convolutional neural networks Hit paper breakdown → | 2020 | 238 |
| 2 | 2020 | 59 | |
| 3 | 2019 | 40 | |
| 4 | 2017 | 28 | |
| 5 | 2022 | 23 | |
| 6 | 2017 | 20 | |
| 7 | 2016 | 16 | |
| 8 | 2008 | 6 | |
| 9 | 2014 | 5 | |
| 10 | 2020 | 2 | |
| 11 | 2024 | 1 | |
| 12 | 2008 | 1 |
About Yan‐Wei Lee
Yan‐Wei Lee is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Pulmonary and Respiratory Medicine, Cancer Research and Biomedical Engineering, having authored 12 papers that have together received 439 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Breast Cancer Treatment Studies (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Ultrasound Imaging and Elastography (2 papers), Photoacoustic and Ultrasonic Imaging (2 papers), COVID-19 diagnosis using AI (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (304 citations), Health Informatics (16 citations), Artificial Intelligence (329 citations), Neurology (60 citations) and Media Technology (34 citations). Yan‐Wei Lee has collaborated with scholars based in Taiwan, South Korea and United States. Frequent co-authors include Ruey‐Feng Chang, Chiun‐Sheng Huang, Woo Kyung Moon, Su Hyun Lee, Yao‐Sian Huang, Chih‐Yen Tu, Min Sun Bae, Chia‐Hung Chen, Wei‐Chih Liao and Su Hyun Lee. Their work appears in journals such as Computer Methods and Programs in Biomedicine, Computers in Biology and Medicine, Artificial Intelligence in Medicine, Medical Physics and Biomedical Signal Processing and Control.
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.