Kai Chen
Impact in
- Cancer Research top 2%
- Breast Cancer Treatment Studies
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- Breast Lesions and Carcinomas
Papers in
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- Breast Cancer Treatment Studies 35
- MicroRNA in disease regulation 2
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- Breast Lesions and Carcinomas 12
- Co-authors
- Fengxi Su (36 shared papers)Liling Zhu (30 shared papers)Erwei Song (21 shared papers)Shunrong Li (27 shared papers)Lisa Kay Jacobs (10 shared papers)Weijuan Jia (16 shared papers)Jieqiong Liu (8 shared papers)Qiang Liu (12 shared papers)
- Journals
- Annals of Surgical Oncology (8 papers)Oncotarget (5 papers)PLoS ONE (4 papers)BMC Cancer (3 papers)European Radiology (3 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Kai Chen
81 papers receiving 2.0k citations
Kai Chen's Hit Papers
Peers
Comparison fields: 5 of 64
- Cancer Research 509
- Pathology and Forensic Medicine 384
- Radiology, Nuclear Medicine and Imaging 373
- Health Informatics 11
- Oncology 98
Countries citing papers authored by Kai Chen
This map shows the geographic impact of Kai Chen'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 Kai Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Chen more than expected).
Fields of papers citing papers by Kai Chen
This network shows the impact of papers produced by Kai Chen. 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 Kai Chen. The network helps show where Kai Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai Chen, 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 85 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 234 | |
| 2 | Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study Hit paper breakdown → | 2021 | 207 |
| 3 | 2019 | 138 | |
| 4 | 2017 | 106 | |
| 5 | 2015 | 101 | |
| 6 | 2014 | 78 | |
| 7 | 2019 | 70 | |
| 8 | 2015 | 53 | |
| 9 | 2013 | 50 | |
| 10 | 2016 | 45 | |
| 11 | 2015 | 40 | |
| 12 | 2016 | 36 | |
| 13 | 2015 | 35 | |
| 14 | 2016 | 34 | |
| 15 | 2017 | 33 | |
| 16 | 2011 | 32 | |
| 17 | 2012 | 30 | |
| 18 | 2017 | 30 | |
| 19 | 2015 | 28 | |
| 20 | 2012 | 27 |
About Kai Chen
Kai Chen is a scholar working on Cancer Research, Pathology and Forensic Medicine, Radiology, Nuclear Medicine and Imaging, Oncology and Otorhinolaryngology, having authored 85 papers that have together received 2.0k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (35 papers), Breast Lesions and Carcinomas (12 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (3 papers), Breast Implant and Reconstruction (2 papers), MicroRNA in disease regulation (2 papers), Head and Neck Cancer Studies (2 papers) and Central Venous Catheters and Hemodialysis (1 paper). The work is most often cited by research in Cancer Research (509 citations), Pathology and Forensic Medicine (384 citations), Radiology, Nuclear Medicine and Imaging (373 citations), Health Informatics (11 citations) and Oncology (98 citations). Kai Chen has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Fengxi Su, Liling Zhu, Erwei Song, Shunrong Li, Lisa Kay Jacobs, Weijuan Jia, Jieqiong Liu, Qiang Liu, Nanyan Rao and Yunjie Zeng. Their work appears in journals such as Annals of Surgical Oncology, Oncotarget, PLoS ONE, BMC Cancer 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.