Fu Shen

1.1k total citations
48 papers, 837 citations indexed

About

Fu Shen is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Fu Shen has authored 48 papers receiving a total of 837 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Oncology, 24 papers in Radiology, Nuclear Medicine and Imaging and 10 papers in Surgery. Recurrent topics in Fu Shen's work include Colorectal Cancer Surgical Treatments (25 papers), Radiomics and Machine Learning in Medical Imaging (24 papers) and Colorectal Cancer Screening and Detection (10 papers). Fu Shen is often cited by papers focused on Colorectal Cancer Surgical Treatments (25 papers), Radiomics and Machine Learning in Medical Imaging (24 papers) and Colorectal Cancer Screening and Detection (10 papers). Fu Shen collaborates with scholars based in China, United States and Singapore. Fu Shen's co-authors include Jianping Lu, Xiaolu Ma, Yuwei Xia, William T. London, Yan Jia, Alison A. Evans, Kenneth H. Buetow, Jun Hu, Wuli Yang and Qihua Li and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Chemical Engineering Journal and International Journal of Molecular Sciences.

In The Last Decade

Fu Shen

46 papers receiving 824 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Fu Shen 353 312 147 138 129 48 837
Andrew S. Mikhail 139 0.4× 157 0.5× 33 0.2× 165 1.2× 556 4.3× 46 1.2k
Kai Temming 104 0.3× 117 0.4× 148 1.0× 160 1.2× 135 1.0× 13 814
Kathleen Mosure 385 1.1× 262 0.8× 47 0.3× 57 0.4× 76 0.6× 10 729
Laura Meléndez‐Alafort 360 1.0× 597 1.9× 189 1.3× 14 0.1× 112 0.9× 75 1.2k
Justin McCallen 154 0.4× 74 0.2× 99 0.7× 37 0.3× 77 0.6× 39 718
James Bausch 148 0.4× 223 0.7× 113 0.8× 139 1.0× 48 0.4× 15 824
Haochen Yao 172 0.5× 99 0.3× 46 0.3× 35 0.3× 245 1.9× 35 815
Guobin Hong 53 0.2× 130 0.4× 63 0.4× 81 0.6× 326 2.5× 35 675
Hongsheng Li 354 1.0× 234 0.8× 94 0.6× 63 0.5× 52 0.4× 67 1.1k
Zhichen Sun 648 1.8× 123 0.4× 196 1.3× 127 0.9× 187 1.4× 32 1.5k

Countries citing papers authored by Fu Shen

Since Specialization
Citations

This map shows the geographic impact of Fu Shen'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 Fu Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fu Shen more than expected).

Fields of papers citing papers by Fu Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fu Shen. 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 Fu Shen. The network helps show where Fu Shen may publish in the future.

Co-authorship network of co-authors of Fu Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Fu Shen. A scholar is included among the top collaborators of Fu Shen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fu Shen. Fu Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ren, Tingting, Yanqing Zhang, Fu Shen, et al.. (2025). Highly selective reduction of CO2 to CH4 mediated by 2D/0D Cs3Bi2Br9/BiOBr heterojunctions with atomic-level intimate interfaces. Chemical Engineering Journal. 522. 167042–167042. 2 indexed citations
2.
Zhang, Qianwen, Zhihui Li, Shaoting Zhang, et al.. (2025). MRI-based habitat analysis for pathologic response prediction after neoadjuvant chemoradiotherapy in rectal cancer: a multicenter study. European Radiology. 36(3). 1671–1685.
3.
Li, Zhihui, Yuan Yuan, Minglu Liu, et al.. (2024). Rectal adenocarcinoma: Ex vivo 9.4T MRI—correlation with histopathologic treatment response to neoadjuvant chemoradiotherapy. Cancer Medicine. 13(15). e70075–e70075. 1 indexed citations
4.
Wang, Wei, Min Kong, Fu Shen, et al.. (2024). Ginsenoside Rg3 targets glycosylation of PD-L1 to enhance anti-tumor immunity in non-small cell lung cancer. Frontiers in Immunology. 15. 1434078–1434078. 11 indexed citations
5.
6.
Yuan, Yuan, Kuo Zheng, Lu Zhou, et al.. (2023). Predictive value of modified MRI-based split scar sign (mrSSS) score for pathological complete response after neoadjuvant chemoradiotherapy for patients with rectal cancer. International Journal of Colorectal Disease. 38(1). 40–40. 8 indexed citations
7.
Ma, Shiyu, Zhihui Li, Qianwen Zhang, et al.. (2023). Deep learning-based clinical-radiomics nomogram for preoperative prediction of lymph node metastasis in patients with rectal cancer: a two-center study. Frontiers in Medicine. 10. 1276672–1276672. 10 indexed citations
8.
Chen, Yukun, Xiaolu Ma, Zhihui Li, et al.. (2022). Predicting Mismatch‐Repair Status in Rectal Cancer Using Multiparametric MRI‐Based Radiomics Models: A Preliminary Study. BioMed Research International. 2022(1). 6623574–6623574. 10 indexed citations
9.
10.
Zhang, Qianwen, Yuan Yuan, Sijie Li, et al.. (2022). A CT-Based Radiomics Model for Evaluating Peritoneal Cancer Index in Peritoneal Metastasis Cases: A Preliminary Study. Academic Radiology. 30(7). 1329–1339. 5 indexed citations
11.
Yuan, Yuan, Xiaolu Ma, Shaoting Zhang, et al.. (2022). Is rectal filling optimal for MRI-based radiomics in preoperative T staging of rectal cancer?. Abdominal Radiology. 47(5). 1741–1749. 5 indexed citations
12.
Yuan, Yuan, Shengnan Ren, Tiegong Wang, et al.. (2021). Differentiating T1a–T1b from T2 in gastric cancer lesions with three different measurement approaches based on contrast-enhanced T1W imaging at 3.0 T. BMC Medical Imaging. 21(1). 140–140. 1 indexed citations
13.
Li, Zhihui, et al.. (2021). Evaluating treatment response to neoadjuvant chemoradiotherapy in rectal cancer using various MRI-based radiomics models. BMC Medical Imaging. 21(1). 30–30. 20 indexed citations
14.
Ma, Xiaolu, Shuai Li, Zhihui Li, et al.. (2020). MRI-Based Radiomics of Rectal Cancer: Assessment of the Local Recurrence at the Site of Anastomosis. Academic Radiology. 28. S87–S94. 24 indexed citations
15.
Shen, Fu, Luguang Chen, Zhihui Li, et al.. (2019). The usefulness of b value threshold map in the evaluation of rectal adenocarcinoma. Abdominal Radiology. 45(2). 332–341. 3 indexed citations
16.
Ma, Xiaolu, Fu Shen, Yan Jia, et al.. (2019). MRI-based radiomics of rectal cancer: preoperative assessment of the pathological features. BMC Medical Imaging. 19(1). 86–86. 74 indexed citations
17.
Shen, Fu, Jianping Lu, Luguang Chen, Zhen Wang, & Yukun Chen. (2016). Diagnostic value of dynamic contrast-enhanced magnetic resonance imaging in rectal cancer and its correlation with tumor differentiation. Molecular and Clinical Oncology. 4(4). 500–506. 22 indexed citations
18.
Zhang, Qing, Jeremy Tey, Zhe Yang, et al.. (2012). Intraoperative Radiotherapy in the Combination of Adjuvant Chemotherapy for the Treatment of pT3N0M0 Rectal Cancer After Radical Surgery. American Journal of Clinical Oncology. 37(1). 8–12. 7 indexed citations
19.
Zhang, Qing, Jeremy Tey, Lihua Peng, et al.. (2011). Adjuvant chemoradiotherapy with or without intraoperative radiotherapy for the treatment of resectable locally advanced gastric adenocarcinoma. Radiotherapy and Oncology. 102(1). 51–55. 13 indexed citations
20.
Evans, Alison A., Anna P. O’Connell, J C Pugh, et al.. (1998). Geographic variation in viral load among hepatitis B carriers with differing risks of hepatocellular carcinoma.. PubMed. 7(7). 559–65. 61 indexed citations

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.

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