Gao Si
Impact in
-
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Medical Imaging Techniques and Applications
- COVID-19 diagnosis using AI
Papers in
-
- MRI in cancer diagnosis 5
- Radiomics and Machine Learning in Medical Imaging 3
- Surgery 7
- Esophageal Cancer Research and Treatment 4
- Scoliosis diagnosis and treatment 3
- Co-authors
- Siyao Du (16 shared papers)Lina Zhang (10 shared papers)Jun Xin (2 shared papers)Hongzan Sun (3 shared papers)Zaiming Lu (2 shared papers)Yuee Teng (2 shared papers)Shu Li (2 shared papers)Can Peng (3 shared papers)
- Journals
- European Spine Journal (3 papers)Journal of Orthopaedic Surgery and Research (2 papers)Journal of Magnetic Resonance Imaging (2 papers)Insights into Imaging (2 papers)European Radiology (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Gao Si
34 papers receiving 413 citations
Peers
Comparison fields: 5 of 56
- Radiology, Nuclear Medicine and Imaging 160
- Health Informatics 5
- Obstetrics and Gynecology 23
- Cancer Research 37
- Otorhinolaryngology 6
Countries citing papers authored by Gao Si
This map shows the geographic impact of Gao Si'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 Gao Si with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gao Si more than expected).
Fields of papers citing papers by Gao Si
This network shows the impact of papers produced by Gao Si. 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 Gao Si. The network helps show where Gao Si may publish in the future.
Co-authors
The 25 scholars most cited alongside Gao Si, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 36 | |
| 2 | 2022 | 35 | |
| 3 | 2019 | 35 | |
| 4 | 2023 | 32 | |
| 5 | 2020 | 29 | |
| 6 | 2020 | 21 | |
| 7 | 2022 | 21 | |
| 8 | 2023 | 19 | |
| 9 | 2018 | 19 | |
| 10 | 2020 | 18 | |
| 11 | 2015 | 15 | |
| 12 | 2019 | 14 | |
| 13 | 2024 | 14 | |
| 14 | 2018 | 14 | |
| 15 | 2018 | 13 | |
| 16 | 2020 | 12 | |
| 17 | 2024 | 9 | |
| 18 | 2020 | 9 | |
| 19 | 2023 | 7 | |
| 20 | 2024 | 6 |
About Gao Si
Gao Si is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery, Molecular Biology, Oncology and Pulmonary and Respiratory Medicine, having authored 38 papers that have together received 418 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (5 papers), Single-cell and spatial transcriptomics (4 papers), Esophageal Cancer Research and Treatment (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Scoliosis diagnosis and treatment (3 papers), Epigenetics and DNA Methylation (2 papers), Tendon Structure and Treatment (2 papers) and Cancer Mechanisms and Therapy (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (160 citations), Health Informatics (5 citations), Obstetrics and Gynecology (23 citations), Cancer Research (37 citations) and Otorhinolaryngology (6 citations). Gao Si has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Siyao Du, Lina Zhang, Jun Xin, Hongzan Sun, Zaiming Lu, Yuee Teng, Shu Li, Can Peng, Song Gao and Miao Sun. Their work appears in journals such as European Spine Journal, Journal of Orthopaedic Surgery and Research, Journal of Magnetic Resonance Imaging, Insights into Imaging and European Radiology.
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.