Yuchen Qiu

2.7k total citations · 2 hit papers
62 papers, 1.8k citations indexed

About

Yuchen Qiu is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yuchen Qiu has authored 62 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Radiology, Nuclear Medicine and Imaging, 35 papers in Artificial Intelligence and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yuchen Qiu's work include AI in cancer detection (34 papers), Radiomics and Machine Learning in Medical Imaging (32 papers) and Digital Radiography and Breast Imaging (7 papers). Yuchen Qiu is often cited by papers focused on AI in cancer detection (34 papers), Radiomics and Machine Learning in Medical Imaging (32 papers) and Digital Radiography and Breast Imaging (7 papers). Yuchen Qiu collaborates with scholars based in United States, China and Mexico. Yuchen Qiu's co-authors include Bin Zheng, Theresa Thai, Hong Liu, Kathleen N. Moore, Robert S. Mannel, Gopichandh Danala, Xuxin Chen, Morteza Heidari, Seyedehnafiseh Mirniaharikandehei and Abolfazl Zargari Khuzani and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.

In The Last Decade

Yuchen Qiu

60 papers receiving 1.7k citations

Hit Papers

align trajectories

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.

Recent advances and clinical applications of deep learning in medical image analysis

2022 564 citations Xuxin Chen, Ximin Wang et al. Medical Image Analysis profile →
Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms

2020 290 citations Morteza Heidari, Seyedehnafiseh Mirniaharikandehei et al. profile →

Peers

Yuchen Qiu

RNMI

CVPR

PRM

Tao Tan China

Ashirbani Saha Canada

Adrien Depeursinge Switzerland

Idit Diamant Israel

Shadi Albarqouni Germany

Inês Domingues Portugal

Shandong Wu United States

Stergios Christodoulidis Switzerland

Ken Chang United States

Assaf Hoogi United States

Tao Tan China

Yuchen Qiu

1.0k ×0.9

RNMI

924 ×1.1

459 ×1.4

CVPR

319 ×1.2

PRM

258 ×1.1

Citations per year, relative to Yuchen Qiu Yuchen Qiu (= 1×) peers Tao Tan

Countries citing papers authored by Yuchen Qiu

Since Specialization

Citations

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

Fields of papers citing papers by Yuchen Qiu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuchen Qiu

This figure shows the co-authorship network connecting the top 25 collaborators of Yuchen Qiu. A scholar is included among the top collaborators of Yuchen Qiu 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 Yuchen Qiu. Yuchen Qiu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Yan, Yuanliang, Zhijie Xu, Chong Wei, et al.. (2025). Molybdenum disulfide induces growth inhibition and autophagy-dependent hepatocyte cell death through directly binding and regulating the activity of MST2. Materials Today Bio. 35. 102394–102394.

Zhang, Ke, Xuxin Chen, Theresa Thai, et al.. (2024). Developing a novel image marker to predict the clinical outcome of neoadjuvant chemotherapy (NACT) for ovarian cancer patients. Computers in Biology and Medicine. 172. 108240–108240. 1 indexed citations

Qiu, Yuchen, et al.. (2024). Damping loss factor identification based on energy finite element method. Measurement. 226. 114114–114114. 1 indexed citations

Mirniaharikandehei, Seyedehnafiseh, et al.. (2023). Automated Quantification of Pneumonia Infected Volume in Lung CT Images: A Comparison with Subjective Assessment of Radiologists. Bioengineering. 10(3). 321–321. 1 indexed citations

Xu, Zhongmou, et al.. (2023). Evaluation of the antiwear‐ability/scratch‐resistance efficacy of makeup products by in vitro test method application. Skin Research and Technology. 29(8). e13420–e13420. 1 indexed citations

Xu, Zhongmou, et al.. (2023). Comparative study of instrumental measurement and sensory evaluation methods for the repairing effect of mildly damaged hair bundles. Skin Research and Technology. 29(7). e13394–e13394. 2 indexed citations

Zhang, Ke, Xuxin Chen, Theresa Thai, et al.. (2023). Evaluating the Effectiveness of 2D and 3D CT Image Features for Predicting Tumor Response to Chemotherapy. Bioengineering. 10(11). 1334–1334. 2 indexed citations

Danala, Gopichandh, et al.. (2022). A Comparison of Computer-Aided Diagnosis Schemes Optimized Using Radiomics and Deep Transfer Learning Methods. Bioengineering. 9(6). 256–256. 22 indexed citations

Jones, Meredith, et al.. (2022). Improving mammography lesion classification by optimal fusion of handcrafted and deep transfer learning features. Physics in Medicine and Biology. 67(5). 54001–54001. 17 indexed citations

10.

Chen, Xuxin, Ximin Wang, Ke Zhang, et al.. (2022). Recent advances and clinical applications of deep learning in medical image analysis. Medical Image Analysis. 79. 102444–102444. 564 indexed citations breakdown →

11.

Chen, Xuxin, Theresa Thai, Camille C. Gunderson, et al.. (2020). Developing a new radiomics-based CT image marker to detect lymph node metastasis among cervical cancer patients. Computer Methods and Programs in Biomedicine. 197. 105759–105759. 28 indexed citations

12.

Chen, Xuxin, et al.. (2019). Applying a new quantitative image analysis scheme based on global mammographic features to assist diagnosis of breast cancer. Computer Methods and Programs in Biomedicine. 179. 104995–104995. 23 indexed citations

13.

Zheng, Bin, et al.. (2019). Developing global image feature analysis models to predict cancer risk and prognosis. SHILAP Revista de lepidopterología. 2(1). 17–17. 5 indexed citations

14.

Zhang, Roy, Theresa Thai, Camille C. Gunderson, et al.. (2018). Classification of Tumor Epithelium and Stroma by Exploiting Image Features Learned by Deep Convolutional Neural Networks. Annals of Biomedical Engineering. 46(12). 1988–1999. 57 indexed citations

15.

Heidari, Morteza, Theresa Thai, Camille C. Gunderson, et al.. (2018). Prediction of chemotherapy response in ovarian cancer patients using a new clustered quantitative image marker. Physics in Medicine and Biology. 63(15). 155020–155020. 26 indexed citations

16.

Danala, Gopichandh, Theresa Thai, Camille C. Gunderson, et al.. (2017). Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to Chemotherapy. Academic Radiology. 24(10). 1233–1239. 36 indexed citations

17.

Yan, Shiju, et al.. (2017). Applying a new bilateral mammographic density segmentation method to improve accuracy of breast cancer risk prediction. International Journal of Computer Assisted Radiology and Surgery. 12(10). 1819–1828. 13 indexed citations

18.

Yan, Shiju, et al.. (2017). Improving Performance of Breast Cancer Risk Prediction by Incorporating Optical Density Image Feature Analysis. Academic Radiology. 29. S199–S210. 6 indexed citations

19.

Wang, Yunzhi, Yuchen Qiu, Theresa Thai, et al.. (2016). Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome. BMC Medical Imaging. 16(1). 52–52. 8 indexed citations

20.

Tan, Maxine, et al.. (2015). Assessment of performance and reproducibility of applying a content‐based image retrieval scheme for classification of breast lesions. Medical Physics. 42(7). 4241–4249. 16 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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