Jiangfen Wu
Impact in
- Health Informatics top 5%
-
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- COVID-19 diagnosis using AI
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 12
- MRI in cancer diagnosis 8
- COVID-19 diagnosis using AI 4
- Genetics 7
- Hemoglobinopathies and Related Disorders 4
- Glioma Diagnosis and Treatment 3
- Co-authors
- Ning Mao (3 shared papers)Mei Yuan (6 shared papers)Lei Chen (2 shared papers)Hai Li (5 shared papers)Chao Sun (2 shared papers)Tongfu Yu (5 shared papers)Yan Zhong (5 shared papers)Chao Zhao (1 shared paper)
- Journals
- Journal of Magnetic Resonance Imaging (8 papers)European Radiology (6 papers)Medicine (3 papers)International Journal of Computer Assisted Radiology and Surgery (2 papers)Medical Physics (1 paper)
- Partner nations
- ChinaUnited StatesSpain
In The Last Decade
Jiangfen Wu
47 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 72
- Health Informatics 31
- Radiology, Nuclear Medicine and Imaging 490
- Pulmonary and Respiratory Medicine 256
- Genetics 60
- Hepatology 43
Countries citing papers authored by Jiangfen Wu
This map shows the geographic impact of Jiangfen 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 Jiangfen Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiangfen Wu more than expected).
Fields of papers citing papers by Jiangfen Wu
This network shows the impact of papers produced by Jiangfen 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 Jiangfen Wu. The network helps show where Jiangfen Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jiangfen 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
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 105 | |
| 2 | 2018 | 102 | |
| 3 | 2015 | 57 | |
| 4 | 2018 | 57 | |
| 5 | 2016 | 44 | |
| 6 | 2017 | 41 | |
| 7 | 2022 | 41 | |
| 8 | 2021 | 41 | |
| 9 | 2016 | 37 | |
| 10 | 2019 | 33 | |
| 11 | 2017 | 32 | |
| 12 | 2020 | 28 | |
| 13 | 2014 | 27 | |
| 14 | 2017 | 26 | |
| 15 | 2022 | 24 | |
| 16 | 2018 | 23 | |
| 17 | 2023 | 22 | |
| 18 | 2019 | 22 | |
| 19 | 2021 | 21 | |
| 20 | 2022 | 21 |
About Jiangfen Wu
Jiangfen Wu is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics, Pulmonary and Respiratory Medicine, Epidemiology and Hematology, having authored 50 papers that have together received 1.0k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (12 papers), MRI in cancer diagnosis (8 papers), COVID-19 diagnosis using AI (4 papers), Hemoglobinopathies and Related Disorders (4 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers), Iron Metabolism and Disorders (3 papers), Glioma Diagnosis and Treatment (3 papers) and Blood groups and transfusion (2 papers). The work is most often cited by research in Health Informatics (31 citations), Radiology, Nuclear Medicine and Imaging (490 citations), Pulmonary and Respiratory Medicine (256 citations), Genetics (60 citations) and Hepatology (43 citations). Jiangfen Wu has collaborated with scholars based in China, United States and Spain. Frequent co-authors include Ning Mao, Mei Yuan, Lei Chen, Hai Li, Chao Sun, Tongfu Yu, Yan Zhong, Chao Zhao, Ping Yin and Weidao Chen. Their work appears in journals such as Journal of Magnetic Resonance Imaging, European Radiology, Medicine, International Journal of Computer Assisted Radiology and Surgery and Medical Physics.
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.