Yanan Wu

552 total citations
33 papers, 342 citations indexed

About

Yanan Wu is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, Yanan Wu has authored 33 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Pulmonary and Respiratory Medicine, 17 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Oncology. Recurrent topics in Yanan Wu's work include Lung Cancer Diagnosis and Treatment (15 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and COVID-19 diagnosis using AI (6 papers). Yanan Wu is often cited by papers focused on Lung Cancer Diagnosis and Treatment (15 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and COVID-19 diagnosis using AI (6 papers). Yanan Wu collaborates with scholars based in China, United States and Hong Kong. Yanan Wu's co-authors include Shouliang Qi, Wei Qian, Shuyue Xia, Yudong Yao, Yu Sun, Yubao Guan, Long Bai, Hongliang Ren, Yin Zhang⋆ and Baihua Zhang and has published in prestigious journals such as Analytical Biochemistry, Scientific Reports and Physics in Medicine and Biology.

In The Last Decade

Yanan Wu

28 papers receiving 332 citations

Peers

Yanan Wu

RNMI

PRM

CVPR

Riqiang Gao United States

Aaron Wu United States

Natascha Claudia D’Amico Italy

Mingyu Kim South Korea

Xiuyuan Xu China

Antônio Carlos da Silva Barros Brazil

Juri Yanase United States

Mingquan Lin United States

Yaniv Bar Israel

Rayan Krishnan United States

Riqiang Gao United States

Yanan Wu

213 ×1.3

RNMI

115 ×0.9

PRM

94 ×1.2

97 ×1.5

CVPR

57 ×1.3

Citations per year, relative to Yanan Wu Yanan Wu (= 1×) peers Riqiang Gao

Countries citing papers authored by Yanan Wu

Since Specialization

Citations

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

Fields of papers citing papers by Yanan Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yanan Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Yanan Wu. A scholar is included among the top collaborators of Yanan Wu 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 Yanan Wu. Yanan Wu 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

Yang, Huan, Wenxi He, Ying Zhang, et al.. (2025). Development of a chemiluminescence enzyme immunoassay (CLEIA) for quantitating L1 protein in HPV vaccines. Analytical Biochemistry. 704. 115889–115889.

Feng, Jie, et al.. (2025). A self-training framework for semi-supervised pulmonary vessel segmentation and its application in COPD. Journal of X-Ray Science and Technology. 34(1). 39–55.

Wu, Yanan, Shuyue Xia, Zhenyu Liang, Rongchang Chen, & Shouliang Qi. (2024). Artificial intelligence in COPD CT images: identification, staging, and quantitation. Respiratory Research. 25(1). 20 indexed citations

Wu, Yanan, Li Shang, Shuyue Xia, et al.. (2024). BreathVisionNet: A pulmonary-function-guided CNN-transformer hybrid model for expiratory CT image synthesis. Computer Methods and Programs in Biomedicine. 259. 108516–108516.

Zhao, Meng, Yanan Wu, Xiaoyu Zhang, et al.. (2024). Learning and depicting lobe-based radiomics feature for COPD Severity staging in low-dose CT images. BMC Pulmonary Medicine. 24(1). 294–294. 3 indexed citations

Wu, Yanan, et al.. (2023). Understanding the role of geographical environments in emergency dispatches with GPS trajectories. Abstracts of the ICA. 6. 1–2. 1 indexed citations

Wu, Yanan, Shouliang Qi, Jie Hou, et al.. (2023). Attention-guided multiple instance learning for COPD identification: To combine the intensity and morphology. Journal of Applied Biomedicine. 43(3). 568–585. 10 indexed citations

Qi, Shouliang, Yanan Wu, Chen Li, et al.. (2023). NCCT-CECT image synthesizers and their application to pulmonary vessel segmentation. Computer Methods and Programs in Biomedicine. 231. 107389–107389. 9 indexed citations

Liu, Yang, et al.. (2023). Tracheal sound-based apnea detection using hidden Markov model in sedated volunteers and post anesthesia care unit patients. Journal of Clinical Monitoring and Computing. 37(4). 1061–1070. 2 indexed citations

10.

Bai, Long, et al.. (2023). Rethinking exemplars for continual semantic segmentation in endoscopy scenes: Entropy-based mini-batch pseudo-replay. Computers in Biology and Medicine. 165. 107412–107412. 9 indexed citations

11.

Wu, Yanan, Shouliang Qi, Jie Feng, et al.. (2023). Two-stage contextual transformer-based convolutional neural network for airway extraction from CT images. Artificial Intelligence in Medicine. 143. 102637–102637. 17 indexed citations

12.

Qi, Shouliang, Yanan Wu, Yong Yue, et al.. (2023). Deep radiomic model based on the sphere–shell partition for predicting treatment response to chemotherapy in lung cancer. Translational Oncology. 35. 101719–101719. 3 indexed citations

13.

Wu, Yanan, et al.. (2022). CoT-XNet: contextual transformer with Xception network for diabetic retinopathy grading. Physics in Medicine and Biology. 67(24). 245003–245003. 27 indexed citations

14.

Wu, Yanan, Shouliang Qi, Chen Li, et al.. (2022). A fully automatic segmentation pipeline of pulmonary lobes before and after lobectomy from computed tomography images. Computers in Biology and Medicine. 147. 105792–105792. 15 indexed citations

15.

Qi, Shouliang, Yanan Wu, Yong Yue, et al.. (2022). Deep multiple instance learning for predicting chemotherapy response in non-small cell lung cancer using pretreatment CT images. Scientific Reports. 12(1). 19829–19829. 10 indexed citations

16.

Zhang, Baihua, et al.. (2022). Multi-scale segmentation squeeze-and-excitation UNet with conditional random field for segmenting lung tumor from CT images. Computer Methods and Programs in Biomedicine. 222. 106946–106946. 35 indexed citations

17.

Qi, Qianqian, Shouliang Qi, Yanan Wu, et al.. (2021). Fully automatic pipeline of convolutional neural networks and capsule networks to distinguish COVID-19 from community-acquired pneumonia via CT images. Computers in Biology and Medicine. 141. 105182–105182. 10 indexed citations

18.

Wu, Yanan, et al.. (2020). The Analysis of How Apnea Influences the Autonomic Nervous System Using Short-Term Heart Rate Variability Indices. Journal of Healthcare Engineering. 2020. 1–8. 5 indexed citations

19.

Zhang, Qin, Jiacheng Chen, Yanan Wu, et al.. (2020). Suppressing SO3 formation in copper smelting flue gas by ejecting pyrite into flue. Environmental Science and Pollution Research. 28(4). 4307–4316. 4 indexed citations

20.

Wu, Yanan, et al.. (2020). Adaptive Filtering Improved Apnea Detection Performance Using Tracheal Sounds in Noisy Environment: A Simulation Study. BioMed Research International. 2020(1). 7429345–7429345. 5 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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