Xiaotang Yang

1.3k total citations · 1 hit paper
33 papers, 913 citations indexed

About

Xiaotang Yang is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Biomedical Engineering. According to data from OpenAlex, Xiaotang Yang has authored 33 papers receiving a total of 913 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Radiology, Nuclear Medicine and Imaging, 13 papers in Oncology and 7 papers in Biomedical Engineering. Recurrent topics in Xiaotang Yang's work include Radiomics and Machine Learning in Medical Imaging (22 papers), Colorectal Cancer Surgical Treatments (8 papers) and Advanced X-ray and CT Imaging (7 papers). Xiaotang Yang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (22 papers), Colorectal Cancer Surgical Treatments (8 papers) and Advanced X-ray and CT Imaging (7 papers). Xiaotang Yang collaborates with scholars based in China, Finland and United Kingdom. Xiaotang Yang's co-authors include Yanfen Cui, Xiaosong Du, Zhao Yang, Jialiang Ren, Zhikai Zhao, Zhongqiang Shi, Dandan Li, Zhenhui Li, Junjie Zhang and Qianqian Du and has published in prestigious journals such as Scientific Reports, Medical Physics and International Journal of Nanomedicine.

In The Last Decade

Xiaotang Yang

30 papers receiving 906 citations

Hit Papers

A CT-based deep learning radiomics nomogram for predictin... 2022 2026 2023 2024 2022 25 50 75 100
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: A multicenter cohort study
    2022 108 citations Yanfen Cui, Jiayi Zhang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaotang Yang China 16 709 368 185 180 138 33 913
Fusheng Ouyang China 13 836 1.2× 186 0.5× 281 1.5× 125 0.7× 171 1.2× 30 1.1k
Lianzhen Zhong China 15 711 1.0× 208 0.6× 389 2.1× 155 0.9× 103 0.7× 22 934
Yuwei Xia China 17 749 1.1× 263 0.7× 288 1.6× 110 0.6× 225 1.6× 72 994
Yun Bian China 20 586 0.8× 595 1.6× 194 1.0× 115 0.6× 112 0.8× 87 1.0k
Jian Zhu China 16 406 0.6× 156 0.4× 300 1.6× 66 0.4× 108 0.8× 69 894
Xueyi Zheng China 9 418 0.6× 102 0.3× 110 0.6× 228 1.3× 101 0.7× 15 605
Hao Yang China 16 449 0.6× 159 0.4× 361 2.0× 72 0.4× 113 0.8× 71 770
Jiajun Deng China 18 536 0.8× 192 0.5× 566 3.1× 132 0.7× 117 0.8× 58 979
Mehdi Alilou United States 13 774 1.1× 238 0.6× 504 2.7× 138 0.8× 171 1.2× 28 891

Countries citing papers authored by Xiaotang Yang

Since Specialization
Citations

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

Fields of papers citing papers by Xiaotang Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaotang Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaotang Yang. A scholar is included among the top collaborators of Xiaotang Yang 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 Xiaotang Yang. Xiaotang Yang 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
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Zhang, Junjie, et al.. (2024). Preoperative MRI Features Associated With Axillary Nodal Burden and Disease-Free Survival in Patients With Early-Stage Breast Cancer. Korean Journal of Radiology. 25(9). 788–788. 2 indexed citations
3.
Xia, Wei, Dandan Li, Wenguang He, et al.. (2024). Multicenter Evaluation of a Weakly Supervised Deep Learning Model for Lymph Node Diagnosis in Rectal Cancer at MRI. Radiology Artificial Intelligence. 6(2). e230152–e230152. 6 indexed citations
4.
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Yang, Bo, Wuli Zhao, Yingjie Ji, et al.. (2023). Design, synthesis and biological evaluation of 2-((4-sulfamoylphenyl)amino)-pyrrolo[2,3-d]pyrimidine derivatives as CDK inhibitors. Journal of Enzyme Inhibition and Medicinal Chemistry. 38(1). 2169282–2169282. 12 indexed citations
6.
Li, Ting, Xiaotang Yang, Lei Xin, et al.. (2023). The maximal contrast-enhanced range of CT for differentiating the WHO pathological subtypes and risk subgroups of thymic epithelial tumors. British Journal of Radiology. 96(1150). 20221076–20221076. 1 indexed citations
7.
Yang, Xiaotang, et al.. (2023). Computer-Aided Screening and Revealing Action Mechanism of Green Tea Polyphenols Intervention in Alzheimer’s Disease. Foods. 12(3). 635–635. 3 indexed citations
8.
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Yang, Xiaotang, et al.. (2022). Contrast-enhanced CT-based radiomics model for differentiating risk subgroups of thymic epithelial tumors. BMC Medical Imaging. 22(1). 37–37. 11 indexed citations
10.
Yang, Xiaotang, et al.. (2022). Dual-energy CT perfusion imaging for differentiating invasive thymomas, thymic carcinomas, and lymphomas in adults. Clinical Radiology. 77(6). e417–e424. 2 indexed citations
11.
Zhang, Jiayi, Yanfen Cui, Kaikai Wei, et al.. (2022). Deep learning predicts resistance to neoadjuvant chemotherapy for locally advanced gastric cancer: a multicenter study. Gastric Cancer. 25(6). 1050–1059. 21 indexed citations
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Cui, Yanfen, Guanghui Wang, Jialiang Ren, et al.. (2021). Radiomics Features at Multiparametric MRI Predict Disease-Free Survival in Patients With Locally Advanced Rectal Cancer. Academic Radiology. 29(8). e128–e138. 24 indexed citations
14.
Cui, Yanfen, Jialiang Ren, Dandan Li, et al.. (2020). Prognostic value of multiparametric MRI-based radiomics model: Potential role for chemotherapeutic benefits in locally advanced rectal cancer. Radiotherapy and Oncology. 154. 161–169. 34 indexed citations
15.
Cui, Yanfen, Huanhuan Liu, Jialiang Ren, et al.. (2020). Development and validation of a MRI-based radiomics signature for prediction of KRAS mutation in rectal cancer. European Radiology. 30(4). 1948–1958. 88 indexed citations
16.
Li, Hongwei, et al.. (2020). <p>The Clinical Prognostic Value of the Neutrophil-to-Lymphocyte Ratio in Brain Metastases from Non–Small Cell Lung Cancer-Harboring EGFR Mutations</p>. Cancer Management and Research. Volume 12. 5659–5665. 8 indexed citations
17.
Shi, Guohua, Jiawen Wang, Yan Qiang, et al.. (2020). Knowledge-guided synthetic medical image adversarial augmentation for ultrasonography thyroid nodule classification. Computer Methods and Programs in Biomedicine. 196. 105611–105611. 53 indexed citations
18.
Zhang, Ruiping, et al.. (2020). Dual-energy CT perfusion imaging for differentiating WHO subtypes of thymic epithelial tumors. Scientific Reports. 10(1). 5511–5511. 13 indexed citations
19.
Zhang, Junjie, et al.. (2018). [MRI findings and pathological features of occult breast cancer].. PubMed. 40(1). 40–45.
20.
Yang, Xiaotang, Ning Huang, Xiaosong Du, et al.. (2015). The initial experience of the upper abdominal CT angiography using low-concentration contrast medium on dual energy spectral CT. Abdominal Imaging. 40(7). 2894–2899. 32 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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