Qingyu Yuan
Impact in
-
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- Health Informatics top 5%
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 16
-
- Gastric Cancer Management and Outcomes 12
- Co-authors
- Lijun Lu (9 shared papers)Quanshi Wang (9 shared papers)Guoxin Li (15 shared papers)Yuming Jiang (16 shared papers)Wenbing Lv (8 shared papers)Chuanli Chen (13 shared papers)Jianhua Ma (5 shared papers)Qianjin Feng (6 shared papers)
- Journals
- Molecular Imaging and Biology (3 papers)European Radiology (2 papers)Radiotherapy and Oncology (2 papers)Cell Reports Medicine (2 papers)The Lancet Digital Health (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Qingyu Yuan
24 papers receiving 930 citations
Qingyu Yuan's Hit Papers
Peers
Comparison fields: 5 of 66
- Radiology, Nuclear Medicine and Imaging 469
- Health Informatics 24
- Otorhinolaryngology 66
- Pulmonary and Respiratory Medicine 254
- Oncology 150
Countries citing papers authored by Qingyu Yuan
This map shows the geographic impact of Qingyu Yuan'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 Qingyu Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingyu Yuan more than expected).
Fields of papers citing papers by Qingyu Yuan
This network shows the impact of papers produced by Qingyu Yuan. 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 Qingyu Yuan. The network helps show where Qingyu Yuan may publish in the future.
Co-authors
The 25 scholars most cited alongside Qingyu Yuan, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study Hit paper breakdown → | 2022 | 113 |
| 2 | 2018 | 107 | |
| 3 | 2021 | 95 | |
| 4 | 2019 | 75 | |
| 5 | 2023 | 74 | |
| 6 | 2019 | 64 | |
| 7 | 2018 | 63 | |
| 8 | 2023 | 62 | |
| 9 | 2019 | 60 | |
| 10 | 2021 | 39 | |
| 11 | 2023 | 32 | |
| 12 | 2021 | 30 | |
| 13 | 2020 | 26 | |
| 14 | 2022 | 25 | |
| 15 | 2021 | 20 | |
| 16 | 2024 | 16 | |
| 17 | 2023 | 14 | |
| 18 | 2023 | 12 | |
| 19 | 2023 | 8 | |
| 20 | 2022 | 8 |
About Qingyu Yuan
Qingyu Yuan is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Oncology, Otorhinolaryngology and Gastroenterology, having authored 25 papers that have together received 951 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (16 papers), Gastric Cancer Management and Outcomes (12 papers), Cancer Immunotherapy and Biomarkers (3 papers), Head and Neck Cancer Studies (2 papers), Cancer Genomics and Diagnostics (2 papers), Gastrointestinal Tumor Research and Treatment (2 papers), DNA Repair Mechanisms (1 paper) and Pancreatic and Hepatic Oncology Research (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (469 citations), Health Informatics (24 citations), Otorhinolaryngology (66 citations), Pulmonary and Respiratory Medicine (254 citations) and Oncology (150 citations). Qingyu Yuan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Lijun Lu, Quanshi Wang, Guoxin Li, Yuming Jiang, Wenbing Lv, Chuanli Chen, Jianhua Ma, Qianjin Feng, Wufan Chen and Ruijiang Li. Their work appears in journals such as Molecular Imaging and Biology, European Radiology, Radiotherapy and Oncology, Cell Reports Medicine and The Lancet Digital Health.
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.