Pengfei Yang

1.5k total citations
38 papers, 1.1k citations indexed

About

Pengfei Yang is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Biomedical Engineering. According to data from OpenAlex, Pengfei Yang has authored 38 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Radiology, Nuclear Medicine and Imaging, 15 papers in Pulmonary and Respiratory Medicine and 8 papers in Biomedical Engineering. Recurrent topics in Pengfei Yang's work include Radiomics and Machine Learning in Medical Imaging (20 papers), Medical Imaging Techniques and Applications (8 papers) and Advanced X-ray and CT Imaging (8 papers). Pengfei Yang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (20 papers), Medical Imaging Techniques and Applications (8 papers) and Advanced X-ray and CT Imaging (8 papers). Pengfei Yang collaborates with scholars based in China, United States and Canada. Pengfei Yang's co-authors include Tianye Niu, Lei Xu, Chen Luo, Wenjie Liang, Qiang Huang, Lele Zhang, Dalong Wan, Mi Huang, Yu Kuang and Yangkang Jiang and has published in prestigious journals such as Clinical Cancer Research, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.

In The Last Decade

Pengfei Yang

38 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
Pengfei Yang China 16 832 402 291 256 220 38 1.1k
Bal Sanghera United Kingdom 15 904 1.1× 306 0.8× 246 0.8× 214 0.8× 239 1.1× 44 1.3k
Sarah Boughdad Switzerland 11 1.1k 1.3× 421 1.0× 294 1.0× 134 0.5× 266 1.2× 32 1.3k
Ida Häggström United States 9 1.2k 1.4× 320 0.8× 181 0.6× 157 0.6× 353 1.6× 20 1.4k
Andrea Delli Pizzi Italy 22 828 1.0× 425 1.1× 571 2.0× 433 1.7× 128 0.6× 78 1.5k
Sylvain Reuzé France 12 1.7k 2.1× 565 1.4× 372 1.3× 195 0.8× 436 2.0× 18 2.0k
J. Castelli France 24 924 1.1× 697 1.7× 208 0.7× 230 0.9× 229 1.0× 99 1.7k
Steve Bandula United Kingdom 14 788 0.9× 265 0.7× 157 0.5× 134 0.5× 351 1.6× 34 1.4k
Jessica Goya-Outi France 4 864 1.0× 317 0.8× 180 0.6× 99 0.4× 189 0.9× 5 964
Junlin Zhou China 18 668 0.8× 353 0.9× 200 0.7× 158 0.6× 229 1.0× 159 1.3k
Zhenchao Tang China 15 1.3k 1.5× 352 0.9× 405 1.4× 143 0.6× 212 1.0× 31 1.5k

Countries citing papers authored by Pengfei Yang

Since Specialization
Citations

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

Fields of papers citing papers by Pengfei Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengfei Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Pengfei Yang. A scholar is included among the top collaborators of Pengfei 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 Pengfei Yang. Pengfei 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
1.
Yang, Pengfei, et al.. (2024). Prediction of SBRT response in liver cancer by combining original and delta cone-beam CT radiomics: a pilot study. Physical and Engineering Sciences in Medicine. 47(1). 295–307. 1 indexed citations
2.
Yang, Pengfei, Zhao Wu, Chen Luo, et al.. (2023). Virtual differential phase‐contrast and dark‐field imaging of x‐ray absorption images via deep learning. Bioengineering & Translational Medicine. 8(6). e10494–e10494. 7 indexed citations
3.
Zhao, Jinling, et al.. (2023). Local wavenumber estimation for small damages based on artificial neural network. NDT & E International. 138. 102866–102866. 3 indexed citations
4.
Yang, Pengfei, et al.. (2022). Four-Dimensional Cone Beam CT Imaging Using a Single Routine Scan via Deep Learning. IEEE Transactions on Medical Imaging. 42(5). 1495–1508. 15 indexed citations
5.
Xu, Lei, Chen Luo, Jing Yang, et al.. (2021). Integrating intratumoral and peritumoral features to predict tumor recurrence in intrahepatic cholangiocarcinoma. Physics in Medicine and Biology. 66(12). 125001–125001. 20 indexed citations
6.
Lin, Peng, Pengfei Yang, Shi Chen, et al.. (2020). A Delta-radiomics model for preoperative evaluation of Neoadjuvant chemotherapy response in high-grade osteosarcoma. Cancer Imaging. 20(1). 7–7. 93 indexed citations
7.
Shen, Xiaoyong, Fan Yang, Pengfei Yang, et al.. (2020). A Contrast-Enhanced Computed Tomography Based Radiomics Approach for Preoperative Differentiation of Pancreatic Cystic Neoplasm Subtypes: A Feasibility Study. Frontiers in Oncology. 10. 248–248. 35 indexed citations
8.
Yang, Pengfei, Chen Luo, Xiaoyong Shen, et al.. (2020). Feasibility of predicting pancreatic neuroendocrine tumor grade using deep features from unsupervised learning. 23–23. 2 indexed citations
9.
Xue, Yi, Chen Luo, Yangkang Jiang, et al.. (2020). Image domain multi-material decomposition using single energy CT. Physics in Medicine and Biology. 65(6). 65014–65014. 6 indexed citations
10.
Xu, Lei, Pengfei Yang, Yangkang Jiang, et al.. (2019). A multi-organ cancer study of the classification performance using 2D and 3D image features in radiomics analysis. Physics in Medicine and Biology. 64(21). 215009–215009. 45 indexed citations
11.
Jiang, Yangkang, Chunlin Yang, Pengfei Yang, et al.. (2019). Scatter correction of cone-beam CT using a deep residual convolution neural network (DRCNN). Physics in Medicine and Biology. 64(14). 145003–145003. 50 indexed citations
12.
Xu, Lei, Pengfei Yang, Wenjie Liang, et al.. (2019). A radiomics approach based on support vector machine using MR images for preoperative lymph node status evaluation in intrahepatic cholangiocarcinoma. Theranostics. 9(18). 5374–5385. 124 indexed citations
13.
Cao, Caineng, et al.. (2019). Feasibility of multiparametric imaging with PET/MR in nasopharyngeal carcinoma: A pilot study. Oral Oncology. 93. 91–95. 14 indexed citations
14.
Zhang, Rui, Lei Xu, Xue Wen, et al.. (2019). A nomogram based on bi-regional radiomics features from multimodal magnetic resonance imaging for preoperative prediction of microvascular invasion in hepatocellular carcinoma. Quantitative Imaging in Medicine and Surgery. 9(9). 1503–1515. 72 indexed citations
15.
Zhang, Xiuming, Yanfeng Bai, Lei Xu, et al.. (2019). Clinical and morpho-molecular classifiers for prediction of hepatocellular carcinoma prognosis and recurrence after surgical resection. Hepatology International. 13(6). 715–725. 7 indexed citations
16.
Zhang, Xiuming, Yanfeng Bai, Lei Xu, et al.. (2019). Clinical and Morpho-Molecular Classifiers for Prediction of Hepatocellular Carcinoma Prognosis and Recurrence After Surgical Resection. SSRN Electronic Journal. 1 indexed citations
17.
Liang, Wenjie, Pengfei Yang, Rui Huang, et al.. (2018). A Combined Nomogram Model to Preoperatively Predict Histologic Grade in Pancreatic Neuroendocrine Tumors. Clinical Cancer Research. 25(2). 584–594. 150 indexed citations
18.
Shen, Xiaoyong, Fan Yang, Pengfei Yang, et al.. (2018). Non-Invasive Diagnosis Model for Pancreatic Cystic Tumors Based on Machine Learning-Radiomics Using Contrast-Enhanced CT. SSRN Electronic Journal. 1 indexed citations
19.
Liang, Wenjie, Lei Xu, Pengfei Yang, et al.. (2018). Novel Nomogram for Preoperative Prediction of Early Recurrence in Intrahepatic Cholangiocarcinoma. Frontiers in Oncology. 8. 360–360. 91 indexed citations
20.
Wu, Yan, Lei Xu, Pengfei Yang, et al.. (2018). Survival Prediction in High-grade Osteosarcoma Using Radiomics of Diagnostic Computed Tomography. EBioMedicine. 34. 27–34. 90 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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