Si‐Min Ruan
Impact in
- Hepatology top 2%
- Hepatocellular Carcinoma Treatment and Prognosis
- Health Informatics top 5%
Papers in
- Hepatology 20
- Hepatocellular Carcinoma Treatment and Prognosis 19
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- Radiomics and Machine Learning in Medical Imaging 12
- MRI in cancer diagnosis 10
- Co-authors
- Ming‐De Lu (28 shared papers)Wei Wang (28 shared papers)Xiaoyan Xie (22 shared papers)Ming Kuang (19 shared papers)Li‐Da Chen (25 shared papers)Xiao-wen Huang (2 shared papers)Yang Huang (11 shared papers)Zhu Wang (5 shared papers)
In The Last Decade
Si‐Min Ruan
40 papers receiving 649 citations
Peers
Comparison fields: 5 of 73
- Hepatology 320
- Health Informatics 39
- Radiology, Nuclear Medicine and Imaging 351
- Epidemiology 171
- Reproductive Medicine 41
Countries citing papers authored by Si‐Min Ruan
This map shows the geographic impact of Si‐Min Ruan'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 Si‐Min Ruan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Si‐Min Ruan more than expected).
Fields of papers citing papers by Si‐Min Ruan
This network shows the impact of papers produced by Si‐Min Ruan. 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 Si‐Min Ruan. The network helps show where Si‐Min Ruan may publish in the future.
Co-authors
The 25 scholars most cited alongside Si‐Min Ruan, 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 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 153 | |
| 2 | 2018 | 94 | |
| 3 | 2021 | 46 | |
| 4 | 2018 | 36 | |
| 5 | 2018 | 30 | |
| 6 | 2023 | 29 | |
| 7 | 2021 | 26 | |
| 8 | 2018 | 26 | |
| 9 | 2020 | 20 | |
| 10 | 2022 | 18 | |
| 11 | 2021 | 17 | |
| 12 | 2018 | 17 | |
| 13 | 2022 | 13 | |
| 14 | 2020 | 13 | |
| 15 | 1997 | 12 | |
| 16 | 2022 | 9 | |
| 17 | 2021 | 9 | |
| 18 | 2021 | 9 | |
| 19 | 2024 | 8 | |
| 20 | 2023 | 8 |
About Si‐Min Ruan
Si‐Min Ruan is a scholar working on Hepatology, Radiology, Nuclear Medicine and Imaging, Oncology, Epidemiology and Biomedical Engineering, having authored 43 papers that have together received 657 indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (19 papers), Radiomics and Machine Learning in Medical Imaging (12 papers), MRI in cancer diagnosis (10 papers), Liver Disease Diagnosis and Treatment (9 papers), AI in cancer detection (4 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (4 papers), Pancreatic and Hepatic Oncology Research (4 papers) and Ultrasound and Hyperthermia Applications (4 papers). The work is most often cited by research in Hepatology (320 citations), Health Informatics (39 citations), Radiology, Nuclear Medicine and Imaging (351 citations), Epidemiology (171 citations) and Reproductive Medicine (41 citations). Si‐Min Ruan has collaborated with scholars based in China, Spain and France. Frequent co-authors include Ming‐De Lu, Wei Wang, Xiaoyan Xie, Ming Kuang, Li‐Da Chen, Xiao-wen Huang, Yang Huang, Zhu Wang, Shuling Chen and Jinyu Liang. Their work appears in journals such as European Radiology, Abdominal Radiology, La radiologia medica, Frontiers in Oncology and Fertility and Sterility.
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.