Jianwei Wang

951 total citations
46 papers, 659 citations indexed

About

Jianwei Wang is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Jianwei Wang has authored 46 papers receiving a total of 659 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Pulmonary and Respiratory Medicine, 22 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Surgery. Recurrent topics in Jianwei Wang's work include Lung Cancer Diagnosis and Treatment (24 papers), Radiomics and Machine Learning in Medical Imaging (16 papers) and Lung Cancer Treatments and Mutations (13 papers). Jianwei Wang is often cited by papers focused on Lung Cancer Diagnosis and Treatment (24 papers), Radiomics and Machine Learning in Medical Imaging (16 papers) and Lung Cancer Treatments and Mutations (13 papers). Jianwei Wang collaborates with scholars based in China, United States and Hong Kong. Jianwei Wang's co-authors include Zhen Zhou, Yizhou Wang, Botong Wu, Yibo Wang, Rutai Hui, Linlin Qi, Ning Wu, Yang Zou, L Zhang and Ming Su and has published in prestigious journals such as Oncogene, Scientific Reports and CHEST Journal.

In The Last Decade

Jianwei Wang

44 papers receiving 649 citations

Peers

Jianwei Wang

PRM

RNMI

SURGE

Stephanie Lee‐Felker United States

Kwon Joong Na South Korea

Hongxiang Feng China

David Kersting Germany

Zhe-Yu Hu China

Xuehong Diao China

Elisa Roca Italy

Hongkun Yin China

Jae Seon Eo South Korea

Zhengrong Zhou China

Stephanie Lee‐Felker United States

Jianwei Wang

324 ×0.9

PRM

262 ×1.0

RNMI

138 ×0.9

77 ×0.7

68 ×0.8

SURGE

Citations per year, relative to Jianwei Wang Jianwei Wang (= 1×) peers Stephanie Lee‐Felker

Countries citing papers authored by Jianwei Wang

Since Specialization

Citations

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

Fields of papers citing papers by Jianwei Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianwei Wang

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

Li, Fenglan, Changfa Xia, Jianing Liu, et al.. (2025). Pulmonary Subsolid Nodules. CHEST Journal. 167(6). 1764–1777. 1 indexed citations

Li, Fenglan, et al.. (2024). Predicting epidermal growth factor receptor mutations in non-small cell lung cancer through dual-layer spectral CT: a prospective study. Insights into Imaging. 15(1). 109–109. 1 indexed citations

Liu, Li, Yao Huang, Jianwei Wang, et al.. (2024). Opportunistic lung cancer screening with low‐dose computed tomography in National Cancer Center of China: The first 14 years' experience. Cancer Medicine. 13(3). e6914–e6914. 6 indexed citations

Qi, Linlin, Xu Qian, Jiaqi Chen, et al.. (2024). A Self-supervised Learning-Based Fine-Grained Classification Model for Distinguishing Malignant From Benign Subcentimeter Solid Pulmonary Nodules. Academic Radiology. 31(11). 4687–4695. 3 indexed citations

Liu, Jianing, Linlin Qi, Yawen Wang, et al.. (2024). Development of a combined radiomics and CT feature-based model for differentiating malignant from benign subcentimeter solid pulmonary nodules. European Radiology Experimental. 8(1). 8–8. 9 indexed citations

Tang, Yanyan, Lina Zhou, Fei Wang, et al.. (2024). Assessing the efficiency of eligibility criteria for low-dose computed tomography lung screening in China according to current guidelines. BMC Medicine. 22(1). 267–267. 4 indexed citations

Jia, Jia, Guochao Zhang, Linlin Qi, et al.. (2024). The Battle for Accuracy: Identifying the Most Effective Grading System for Lung Invasive Mucinous Adenocarcinoma. Annals of Surgical Oncology. 31(9). 5717–5728. 1 indexed citations

Qi, Linlin, Jia Jia, Guochao Zhang, et al.. (2024). Radiological Features of Primary Pulmonary Invasive Mucinous Adenocarcinoma Based on 312 Consecutive Patients. The Clinical Respiratory Journal. 18(8). e13820–e13820.

Zhang, Li, Jingwen Ma, Jianwei Wang, et al.. (2024). The blind spots on chest computed tomography: what do we miss. Journal of Thoracic Disease. 16(12). 8782–8795.

10.

Liu, Jianing, Linlin Qi, Fenglan Li, et al.. (2023). Diagnostic performance of a deep learning-based method in differentiating malignant from benign subcentimeter (≤10 mm) solid pulmonary nodules. Journal of Thoracic Disease. 15(10). 5475–5484. 6 indexed citations

11.

Qi, Linlin, Wenwen Lu, Lin Yang, et al.. (2019). Qualitative and quantitative imaging features of pulmonary subsolid nodules: differentiating invasive adenocarcinoma from minimally invasive adenocarcinoma and preinvasive lesions. Journal of Thoracic Disease. 11(11). 4835–4846. 14 indexed citations

12.

Zhao, Qing, Jianwei Wang, Lin Yang, Liyan Xue, & Wenwen Lu. (2018). CT diagnosis of pleural and stromal invasion in malignant subpleural pure ground-glass nodules: an exploratory study. European Radiology. 29(1). 279–286. 36 indexed citations

13.

Li, Meng, Ning Wu, Li Zhang, et al.. (2017). Pathologic N0 Status in Clinical T1N0M0 Lung Adenocarcinoma is Predictable by the Solid Component Proportion with Quantitative CT Number Analysis. Scientific Reports. 7(1). 16810–16810. 4 indexed citations

14.

Su, Rui, Lei Dong, Hua Zhao, et al.. (2016). microRNA-23a, -27a and -24 synergistically regulate JAK1/Stat3 cascade and serve as novel therapeutic targets in human acute erythroid leukemia. Oncogene. 35(46). 6001–6014. 30 indexed citations

15.

Tang, Wei, Ning Wu, Yao Huang, et al.. (2014). [Results of low-dose computed tomography (LDCT) screening for early lung cancer: prevalence in 4 690 asymptomatic participants].. PubMed. 36(7). 549–54. 29 indexed citations

16.

Su, Ming, Jianwei Wang, C Wang, et al.. (2014). MicroRNA-221 inhibits autophagy and promotes heart failure by modulating the p27/CDK2/mTOR axis. Cell Death and Differentiation. 22(6). 986–999. 139 indexed citations

17.

Lu, Shanshan, Sheng Liu, Qing‐Quan Zu, et al.. (2013). Multimodal magnetic resonance imaging for assessing lacunar infarction after proximal middle cerebral artery occlusion in a canine model. Chinese Medical Journal. 126(2). 311–317. 3 indexed citations

18.

Wang, Jianwei, et al.. (2012). Computer-aided detection of nodule in low-dose CT screening for lung cancer. Zhonghua fangshexian yixue zazhi. 46(7). 619–623. 2 indexed citations

19.

Tang, Wei, et al.. (2011). The optimization of low-dose scanning protocols of 64-slice spiral CT in the adult chest: a multicenter study. Zhonghua fangshexian yixue zazhi. 45(2). 142–148. 1 indexed citations

20.

Wang, Jianwei. (2000). [Results of phase III clinical trial of zeng sheng-ping in the treatment of patients with esophageal epithelial hyperplasia].. PubMed. 22(6). 510–2. 7 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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