Steven Xu
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Monoclonal and Polyclonal Antibodies Research
Papers in
- Oncology 18
- CAR-T cell therapy research 6
- Cancer Immunotherapy and Biomarkers 6
- Colorectal Cancer Screening and Detection 5
-
- Radiomics and Machine Learning in Medical Imaging 6
- Monoclonal and Polyclonal Antibodies Research 6
- Co-authors
- Min Yuan (9 shared papers)Hong Zhang (6 shared papers)Xingyu Li (6 shared papers)Huizhi Liang (1 shared paper)Jitendra Jonnagaddala (5 shared papers)Timothy Baldwin (1 shared paper)Honghui Zhou (3 shared papers)Zihan Chen (1 shared paper)
- Journals
- Blood (3 papers)Cancer Research (3 papers)JCO Precision Oncology (2 papers)Clinical Pharmacology & Therapeutics (2 papers)Journal of Clinical Oncology (2 papers)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Steven Xu
32 papers receiving 205 citations
Peers
Comparison fields: 5 of 69
- Radiology, Nuclear Medicine and Imaging 61
- Health Informatics 3
- Oncology 55
- Artificial Intelligence 55
- Cancer Research 25
Countries citing papers authored by Steven Xu
This map shows the geographic impact of Steven Xu'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 Steven Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven Xu more than expected).
Fields of papers citing papers by Steven Xu
This network shows the impact of papers produced by Steven Xu. 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 Steven Xu. The network helps show where Steven Xu may publish in the future.
Co-authors
The 25 scholars most cited alongside Steven Xu, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 26 | |
| 2 | 2016 | 23 | |
| 3 | 2022 | 18 | |
| 4 | 2023 | 16 | |
| 5 | 2015 | 16 | |
| 6 | 2022 | 11 | |
| 7 | 2022 | 11 | |
| 8 | 2024 | 9 | |
| 9 | 2022 | 9 | |
| 10 | 2023 | 7 | |
| 11 | 2018 | 7 | |
| 12 | 2024 | 6 | |
| 13 | 2023 | 6 | |
| 14 | 2023 | 6 | |
| 15 | 2016 | 4 | |
| 16 | 2023 | 4 | |
| 17 | 2023 | 4 | |
| 18 | 2019 | 3 | |
| 19 | 2023 | 3 | |
| 20 | 2018 | 3 |
About Steven Xu
Steven Xu is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging, Cancer Research, Immunology and Molecular Biology, having authored 33 papers that have together received 212 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (8 papers), CAR-T cell therapy research (6 papers), Biosimilars and Bioanalytical Methods (6 papers), Cancer Immunotherapy and Biomarkers (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Colorectal Cancer Screening and Detection (5 papers) and Lung Cancer Treatments and Mutations (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (61 citations), Health Informatics (3 citations), Oncology (55 citations), Artificial Intelligence (55 citations) and Cancer Research (25 citations). Steven Xu has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Min Yuan, Hong Zhang, Xingyu Li, Huizhi Liang, Jitendra Jonnagaddala, Timothy Baldwin, Honghui Zhou, Zihan Chen, Miaomiao Yang and Liping Zhang. Their work appears in journals such as Blood, Cancer Research, JCO Precision Oncology, Clinical Pharmacology & Therapeutics and Journal of Clinical Oncology.
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.