Yaqi Shen

1.6k total citations
90 papers, 1.2k citations indexed

About

Yaqi Shen is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Oncology. According to data from OpenAlex, Yaqi Shen has authored 90 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Radiology, Nuclear Medicine and Imaging, 24 papers in Surgery and 18 papers in Oncology. Recurrent topics in Yaqi Shen's work include MRI in cancer diagnosis (24 papers), Radiomics and Machine Learning in Medical Imaging (16 papers) and Colorectal Cancer Surgical Treatments (9 papers). Yaqi Shen is often cited by papers focused on MRI in cancer diagnosis (24 papers), Radiomics and Machine Learning in Medical Imaging (16 papers) and Colorectal Cancer Surgical Treatments (9 papers). Yaqi Shen collaborates with scholars based in China, United States and Hong Kong. Yaqi Shen's co-authors include Daoyu Hu, Zhen Li, Xuemei Hu, Ihab R. Kamel, John N. Morelli, Val M. Runge, F Goerner, Dapeng Hao, Xiaoming Li and Yanchun Wang and has published in prestigious journals such as Scientific Reports, Annals of Oncology and American Journal of Roentgenology.

In The Last Decade

Yaqi Shen

85 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yaqi Shen China 19 573 246 210 166 148 90 1.2k
S E Seltzer United States 16 424 0.7× 413 1.7× 67 0.3× 239 1.4× 96 0.6× 27 1.2k
Andreu F. Costa Canada 18 511 0.9× 217 0.9× 119 0.6× 224 1.3× 117 0.8× 61 1.1k
Po‐Chin Liang Taiwan 26 190 0.3× 648 2.6× 377 1.8× 308 1.9× 201 1.4× 112 1.9k
Jun Aoki Japan 25 361 0.6× 293 1.2× 191 0.9× 561 3.4× 137 0.9× 88 1.9k
Mitsuru Matsuki Japan 26 995 1.7× 529 2.2× 304 1.4× 480 2.9× 292 2.0× 102 1.9k
Jean‐François Deux France 26 1.0k 1.8× 350 1.4× 157 0.7× 302 1.8× 168 1.1× 122 2.7k
George R. Schade United States 21 315 0.5× 264 1.1× 163 0.8× 294 1.8× 620 4.2× 105 1.3k
Kiyoko Kusakabe Japan 18 455 0.8× 263 1.1× 87 0.4× 271 1.6× 124 0.8× 86 1.1k
Linxue Qian China 21 347 0.6× 629 2.6× 112 0.5× 297 1.8× 435 2.9× 115 1.6k
J. Daniel Bourland United States 22 437 0.8× 181 0.7× 125 0.6× 462 2.8× 156 1.1× 83 1.3k

Countries citing papers authored by Yaqi Shen

Since Specialization
Citations

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

Fields of papers citing papers by Yaqi Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yaqi Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Yaqi Shen. A scholar is included among the top collaborators of Yaqi 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 Yaqi Shen. Yaqi 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.
Chen, Jun, Yufan Wang, Xuemei Hu, et al.. (2024). Optimizing CT Esophagography: Ex Vivo Study on Contrast Ratios, Image Quality, and Dual-Energy Benefits. Bioengineering. 11(12). 1300–1300. 2 indexed citations
2.
Zhu, Yun, Le Hui, Yaqi Shen, & Jin Xie. (2024). SPGroup3D: Superpoint Grouping Network for Indoor 3D Object Detection. Proceedings of the AAAI Conference on Artificial Intelligence. 38(7). 7811–7819. 3 indexed citations
3.
Wang, Yanchun, et al.. (2023). Reduced field-of-view DWI‑derived clinical–radiomics model for the prediction of stage in cervical cancer. Insights into Imaging. 14(1). 18–18. 5 indexed citations
4.
Hu, Mingzhe, Yaqi Shen, Heping Yu, et al.. (2023). Prognostic value of cardiac magnetic resonance imaging feature tracking technology in patients with light chain amyloidosis. Clinical Radiology. 79(2). e239–e246. 1 indexed citations
5.
Meng, Xiaoyan, Jiali Li, Yaqi Shen, et al.. (2023). Amide Proton Transfer-Weighted Imaging Combined with ZOOMit Diffusion Kurtosis Imaging in Predicting Lymph Node Metastasis of Cervical Cancer. Bioengineering. 10(3). 331–331. 4 indexed citations
6.
7.
Li, Yuanqiu, Jun Chen, Yaqi Shen, et al.. (2023). Enhancing the Differentiation between Intestinal Behçet’s Disease and Crohn’s Disease through Quantitative Computed Tomography Analysis. Bioengineering. 10(10). 1211–1211. 2 indexed citations
8.
Yang, Peng, Jiali Li, Xuemei Hu, et al.. (2023). Assessing the histopathological features of rectal adenocarcinoma with chemical shift–encoded sequence (CSE)-MRI and diffusion-weighted imaging (DWI). Quantitative Imaging in Medicine and Surgery. 13(5). 3199–3212. 3 indexed citations
9.
Liu, Jialin, Yong Zhou, Lianhong Wang, et al.. (2022). Cytological Analysis and Fine Mapping of paa1 (Post-meiosis Abnormal Anther 1) Mutant with Abnormal Tapetum and Microspore Development. Biochemical Genetics. 60(6). 2268–2285. 2 indexed citations
10.
Li, Yuanqiu, Xuemei Hu, Daoyu Hu, et al.. (2022). The relationship between perianal fistula activity and abdominal adipose tissue in Crohn’s disease: an observational study. Insights into Imaging. 13(1). 156–156. 11 indexed citations
11.
Yang, Yang, Wei Zhou, Daoyu Hu, et al.. (2022). DWI-based radiomic signature: potential role for individualized adjuvant chemotherapy in intrahepatic cholangiocarcinoma after partial hepatectomy. Insights into Imaging. 13(1). 37–37. 5 indexed citations
12.
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Lu, Jingyu, Hao Yu, Zhen Li, et al.. (2019). Apparent diffusion coefficient-based histogram analysis differentiates histological subtypes of periampullary adenocarcinoma. World Journal of Gastroenterology. 25(40). 6116–6128. 7 indexed citations
15.
Yang, Peng, Hao Tang, Xiaoyan Meng, et al.. (2019). Histological grades of rectal cancer: whole-volume histogram analysis of apparent diffusion coefficient based on reduced field-of-view diffusion-weighted imaging. Quantitative Imaging in Medicine and Surgery. 10(1). 243–256. 22 indexed citations
16.
17.
Shen, Yaqi, et al.. (2017). [Relationship of lipid accumulation product with hypertension and diabetes among Beijing residents study].. PubMed. 51(5). 415–420. 6 indexed citations
18.
Xu, Nan, L. Zhang, Feipeng Xiao, et al.. (2017). Transluminal attenuation gradient and corrected models in coronary CT angiography for determining stenosis severity: a primary study using dual-source CT. Clinical Radiology. 72(6). 508–516. 5 indexed citations
19.
Meng, Xiaoyan, Yaqi Shen, Xuemei Hu, et al.. (2017). Differentiating malignant from benign gastric mucosal lesions with quantitative analysis in dual energy spectral computed tomography. Medicine. 96(2). e5878–e5878. 14 indexed citations
20.
Meng, Xiaoyan, Xiaohong Chen, Yaqi Shen, et al.. (2016). Proton-density fat fraction measurement: A viable quantitative biomarker for differentiating adrenal adenomas from nonadenomas. European Journal of Radiology. 86. 112–118. 7 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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