Fa Wu
- Health Informatics top 1%
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- Radiomics and Machine Learning in Medical Imaging 5
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- Medical Image Segmentation Techniques 6
- Advanced Neural Network Applications 3
- Artificial Intelligence top 5%
- AI in cancer detection 3
- Reinforcement Learning in Robotics 2
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- Thyroid Cancer Diagnosis and Treatment 4
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- Medical Imaging and Analysis 4
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- Force Microscopy Techniques and Applications 1
Fa Wu
17 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 88
- Health Informatics 101
- Radiology, Nuclear Medicine and Imaging 692
- Computer Vision and Pattern Recognition 333
- Artificial Intelligence 471
- Endocrinology, Diabetes and Metabolism 181
Countries citing papers authored by Fa Wu
This map shows the geographic impact of Fa Wu'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 Fa Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fa Wu more than expected).
Fields of papers citing papers by Fa Wu
This network shows the impact of papers produced by Fa Wu. 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 Fa Wu. The network helps show where Fa Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fa Wu, 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 | 2024 | 2 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 5 | |
| 4 | 2022 | 5 | |
| 5 | 2022 | 1 | |
| 6 | 2021 | 21 | |
| 7 | 2020 | 1 | |
| 8 | 2020 | 15 | |
| 9 | 2018 | 23 | |
| 10 | 2018 | 1 | |
| 11 | 2017 | 0 | |
| 12 | 2017 | 137 | |
| 13 | 2017 | 103 | |
| 14 | 2016 | 153 | |
| 15 | 2016 | 206 | |
| 16 | 2016 | 162 | |
| 17 | 2016 | 216 | |
| 18 | 2016 | 1 | |
| 19 | 2013 | 1 |
About Fa Wu
Fa Wu is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Endocrinology, Diabetes and Metabolism, having authored 19 papers that have together received 1.1k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Imaging and Analysis (4 papers), Thyroid Cancer Diagnosis and Treatment (4 papers), AI in cancer detection (3 papers), Advanced Neural Network Applications (3 papers), Reinforcement Learning in Robotics (2 papers) and Force Microscopy Techniques and Applications (1 paper). The work is most often cited by research in Health Informatics (101 citations), Radiology, Nuclear Medicine and Imaging (692 citations) and Computer Vision and Pattern Recognition (333 citations). Fa Wu has collaborated with scholars based in China, Hong Kong and Canada. Frequent co-authors include De-Xing Kong, Peijun Hu, Jinlian Ma, Jiang Zhu, Jialin Peng, Tianan Jiang, Dexing Kong, Lu Fang, Zhiyi Peng and Dong Xu. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, Medical Physics, Physics in Medicine and Biology, Computers in Biology and Medicine and Diamond and Related Materials.
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.