Danke Su
Impact in
- Otorhinolaryngology top 10%
- Head and Neck Cancer Studies
- Hepatology top 10%
- Hepatocellular Carcinoma Treatment and Prognosis
Papers in
-
- MRI in cancer diagnosis 17
- Radiomics and Machine Learning in Medical Imaging 15
- Medical Imaging Techniques and Applications 9
-
- Nanoplatforms for cancer theranostics 5
- Co-authors
- Guanqiao Jin (16 shared papers)Lidong Liu (9 shared papers)Dong Xie (6 shared papers)Junjie Liu (4 shared papers)Hai Liao (5 shared papers)Duo Wang (2 shared papers)Kun Zhang (2 shared papers)Xiangyang Huang (7 shared papers)
- Journals
- Medicine (4 papers)European Radiology (3 papers)Frontiers in Immunology (2 papers)OncoTargets and Therapy (2 papers)Oncotarget (2 papers)
- Partner nations
- ChinaUnited States
In The Last Decade
Danke Su
43 papers receiving 508 citations
Peers
Comparison fields: 5 of 76
- Otorhinolaryngology 51
- Hepatology 75
- Radiology, Nuclear Medicine and Imaging 217
- Cancer Research 70
- Biomedical Engineering 163
Countries citing papers authored by Danke Su
This map shows the geographic impact of Danke Su'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 Danke Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danke Su more than expected).
Fields of papers citing papers by Danke Su
This network shows the impact of papers produced by Danke Su. 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 Danke Su. The network helps show where Danke Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Danke Su, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 88 | |
| 2 | 2013 | 52 | |
| 3 | 2022 | 37 | |
| 4 | 2017 | 27 | |
| 5 | 2021 | 25 | |
| 6 | 2017 | 21 | |
| 7 | 2022 | 16 | |
| 8 | 2019 | 16 | |
| 9 | 2020 | 16 | |
| 10 | 2024 | 16 | |
| 11 | 2015 | 15 | |
| 12 | 2021 | 14 | |
| 13 | 2018 | 14 | |
| 14 | 2018 | 12 | |
| 15 | Diagnostic performance of ADCs in different ROIs for breast lesions. | 2015 | 12 |
| 16 | 2020 | 10 | |
| 17 | 2010 | 9 | |
| 18 | 2021 | 8 | |
| 19 | 2019 | 8 | |
| 20 | 2020 | 7 |
About Danke Su
Danke Su is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Otorhinolaryngology, Pulmonary and Respiratory Medicine and Hepatology, having authored 45 papers that have together received 517 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (17 papers), Radiomics and Machine Learning in Medical Imaging (15 papers), Medical Imaging Techniques and Applications (9 papers), Head and Neck Cancer Studies (7 papers), Hepatocellular Carcinoma Treatment and Prognosis (6 papers), Nanoplatforms for cancer theranostics (5 papers), AI in cancer detection (4 papers) and Nanoparticle-Based Drug Delivery (4 papers). The work is most often cited by research in Otorhinolaryngology (51 citations), Hepatology (75 citations), Radiology, Nuclear Medicine and Imaging (217 citations), Cancer Research (70 citations) and Biomedical Engineering (163 citations). Danke Su has collaborated with scholars based in China and United States. Frequent co-authors include Guanqiao Jin, Lidong Liu, Dong Xie, Junjie Liu, Hai Liao, Duo Wang, Kun Zhang, Xiangyang Huang, Li Ye and Hongxue Li. Their work appears in journals such as Medicine, European Radiology, Frontiers in Immunology, OncoTargets and Therapy and Oncotarget.
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.