Yehang Chen

579 total citations
26 papers, 382 citations indexed

About

Yehang Chen is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Yehang Chen has authored 26 papers receiving a total of 382 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Pulmonary and Respiratory Medicine and 5 papers in Artificial Intelligence. Recurrent topics in Yehang Chen's work include Radiomics and Machine Learning in Medical Imaging (21 papers), Lung Cancer Diagnosis and Treatment (8 papers) and AI in cancer detection (4 papers). Yehang Chen is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (21 papers), Lung Cancer Diagnosis and Treatment (8 papers) and AI in cancer detection (4 papers). Yehang Chen collaborates with scholars based in China, United States and Canada. Yehang Chen's co-authors include Wansheng Long, Bao Feng, Xiangmeng Chen, Zhuangsheng Liu, Ronggang Li, Enming Cui, Kunwei Li, Kunfeng Liu, Zhi Li and Xueguo Liu and has published in prestigious journals such as Nature Communications, Journal of Magnetic Resonance Imaging and Frontiers in Human Neuroscience.

In The Last Decade

Yehang Chen

23 papers receiving 379 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yehang Chen China 10 318 174 81 76 38 26 382
Bao Feng China 10 345 1.1× 202 1.2× 85 1.0× 80 1.1× 40 1.1× 32 413
Zhuangsheng Liu China 10 269 0.8× 133 0.8× 61 0.8× 71 0.9× 26 0.7× 17 334
Juebin Jin China 12 307 1.0× 116 0.7× 49 0.6× 49 0.6× 72 1.9× 25 387
Camilla Scapicchio Italy 5 254 0.8× 70 0.4× 85 1.0× 68 0.9× 41 1.1× 9 336
Khashayar Namdar Canada 10 280 0.9× 109 0.6× 71 0.9× 81 1.1× 64 1.7× 26 470
José Raniery Ferreira Brazil 12 382 1.2× 221 1.3× 103 1.3× 146 1.9× 39 1.0× 29 554
Joanne Hoffman United States 5 259 0.8× 147 0.8× 97 1.2× 126 1.7× 39 1.0× 7 415
Gaia Ninatti Italy 8 182 0.6× 72 0.4× 51 0.6× 49 0.6× 20 0.5× 18 249
Johanna Uthoff United States 10 271 0.9× 262 1.5× 85 1.0× 73 1.0× 16 0.4× 15 404
Murilo Falleiros Lemos Schmitt Brazil 3 359 1.1× 100 0.6× 93 1.1× 66 0.9× 28 0.7× 5 392

Countries citing papers authored by Yehang Chen

Since Specialization
Citations

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

Fields of papers citing papers by Yehang Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yehang Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Yehang Chen. A scholar is included among the top collaborators of Yehang Chen 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 Yehang Chen. Yehang Chen 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, Yehang, Yuan Chen, Peijun Li, et al.. (2025). General lightweight framework for vision foundation model supporting multi-task and multi-center medical image analysis. Nature Communications. 16(1). 2097–2097. 5 indexed citations
2.
He, Jing, et al.. (2025). Single-channel attention classification algorithm based on robust Kalman filtering and norm-constrained ELM. Frontiers in Human Neuroscience. 18. 1481493–1481493. 1 indexed citations
3.
4.
Feng, Bao, Zhiqi Yang, Shi‐Ting Feng, et al.. (2024). Robustly federated learning model for identifying high-risk patients with postoperative gastric cancer recurrence. Nature Communications. 15(1). 742–742. 25 indexed citations
5.
Feng, Bao, Yehang Chen, Xiaojuan Chen, et al.. (2024). Multimodal deep learning radiomics model for predicting postoperative progression in solid stage I non-small cell lung cancer. Cancer Imaging. 24(1). 140–140. 4 indexed citations
6.
Chen, Xiangmeng, Bao Feng, Yehang Chen, et al.. (2023). Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes. European Radiology. 33(10). 6804–6816. 8 indexed citations
7.
Feng, Bao, Xiangmeng Chen, Yehang Chen, et al.. (2023). Identifying Solitary Granulomatous Nodules from Solid Lung Adenocarcinoma: Exploring Robust Image Features with Cross-Domain Transfer Learning. Cancers. 15(3). 892–892. 8 indexed citations
8.
9.
10.
Feng, Bao, Yu Liu, Yehang Chen, et al.. (2022). A Transfer Learning Radiomics Nomogram for Preoperative Prediction of Borrmann Type IV Gastric Cancer From Primary Gastric Lymphoma. Frontiers in Oncology. 11. 802205–802205. 23 indexed citations
11.
Feng, Bao, Zhuangsheng Liu, Yu Liu, et al.. (2022). Predicting lymphovascular invasion in clinically node-negative breast cancer detected by abbreviated magnetic resonance imaging: Transfer learning vs. radiomics. Frontiers in Oncology. 12. 890659–890659. 7 indexed citations
12.
Chen, Yehang & Xiangmeng Chen. (2022). A brain-like classification method for computed tomography images based on adaptive feature matching dual-source domain heterogeneous transfer learning. Frontiers in Human Neuroscience. 16. 1019564–1019564. 1 indexed citations
13.
Chen, Xiangmeng, Bao Feng, Yehang Chen, et al.. (2021). A CT-based deep learning model for subsolid pulmonary nodules to distinguish minimally invasive adenocarcinoma and invasive adenocarcinoma. European Journal of Radiology. 145. 110041–110041. 4 indexed citations
14.
Feng, Bao, Yü Liu, Yehang Chen, et al.. (2021). Computed Tomography-Based Radiomics Nomogram: Potential to Predict Local Recurrence of Gastric Cancer After Radical Resection. Frontiers in Oncology. 11. 638362–638362. 13 indexed citations
15.
Liu, Zhuangsheng, Xiaoping Li, Bao Feng, et al.. (2020). MIP image derived from abbreviated breast MRI: potential to reduce unnecessary sub-nipple biopsies during nipple-sparing mastectomy for breast cancer. European Radiology. 31(6). 3683–3692. 9 indexed citations
16.
Feng, Bao, Xiangmeng Chen, Yehang Chen, et al.. (2020). Radiomics nomogram for preoperative differentiation of lung tuberculoma from adenocarcinoma in solitary pulmonary solid nodule. European Journal of Radiology. 128. 109022–109022. 48 indexed citations
17.
Chen, Xiangmeng, Bao Feng, Yehang Chen, et al.. (2020). A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules. Cancer Imaging. 20(1). 45–45. 35 indexed citations
18.
Feng, Bao, Yehang Chen, Kunfeng Liu, et al.. (2020). Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas. European Radiology. 30(12). 6497–6507. 50 indexed citations
19.
Chen, Xiangmeng, et al.. (2020). Segmentation of small ground glass opacity pulmonary nodules based on Markov random field energy and Bayesian probability difference. BioMedical Engineering OnLine. 19(1). 51–51. 11 indexed citations
20.
Chen, Xiangmeng, Bao Feng, Yehang Chen, et al.. (2019). Whole-Lesion Computed Tomography–Based Entropy Parameters for the Differentiation of Minimally Invasive and Invasive Adenocarcinomas Appearing as Pulmonary Subsolid Nodules. Journal of Computer Assisted Tomography. 43(5). 817–824. 6 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Bao Feng Breakdown of academic impact, for papers by Zhuangsheng Liu Breakdown of academic impact, for papers by Juebin Jin Breakdown of academic impact, for papers by Camilla Scapicchio Breakdown of academic impact, for papers by Khashayar Namdar Breakdown of academic impact, for papers by José Raniery Ferreira Breakdown of academic impact, for papers by Joanne Hoffman Breakdown of academic impact, for papers by Gaia Ninatti Breakdown of academic impact, for papers by Johanna Uthoff Breakdown of academic impact, for papers by Murilo Falleiros Lemos Schmitt
Rankless by CCL
2026