Jingwei Wei

4.1k total citations · 1 hit paper
56 papers, 2.8k citations indexed

About

Jingwei Wei is a scholar working on Radiology, Nuclear Medicine and Imaging, Hepatology and Biomedical Engineering. According to data from OpenAlex, Jingwei Wei has authored 56 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Radiology, Nuclear Medicine and Imaging, 23 papers in Hepatology and 18 papers in Biomedical Engineering. Recurrent topics in Jingwei Wei's work include Radiomics and Machine Learning in Medical Imaging (38 papers), Hepatocellular Carcinoma Treatment and Prognosis (23 papers) and Advanced X-ray and CT Imaging (8 papers). Jingwei Wei is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (38 papers), Hepatocellular Carcinoma Treatment and Prognosis (23 papers) and Advanced X-ray and CT Imaging (8 papers). Jingwei Wei collaborates with scholars based in China, United States and Canada. Jingwei Wei's co-authors include Jie Tian, Dongsheng Gu, Di Dong, Zhenyu Liu, Kai Sun, Cheng Fang, Bo Li, Meiyun Wang, Longfei Li and Shuo Wang and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Analytical Chemistry.

In The Last Decade

Jingwei Wei

51 papers receiving 2.8k 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.

The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges

2019 658 citations Zhenyu Liu, Shuo Wang et al. Theranostics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jingwei Wei China	24	2.2k	891	744	556	491	56	2.8k
MingDe Lin United States	37	2.0k 0.9×	1.7k 1.9×	925 1.2×	547 1.0×	799 1.6×	152	4.0k
Yvonka van Wijk Netherlands	8	3.5k 1.6×	304 0.3×	1.4k 1.9×	751 1.4×	911 1.9×	14	4.0k
Aniek J.G. Even Netherlands	14	3.7k 1.7×	310 0.3×	1.5k 2.0×	806 1.4×	962 2.0×	21	4.3k
Tim Lustberg Netherlands	11	3.8k 1.7×	305 0.3×	1.5k 2.0×	743 1.3×	1.0k 2.1×	17	4.3k
Evelyn E.C. de Jong Netherlands	12	4.0k 1.8×	320 0.4×	1.6k 2.1×	870 1.6×	1.1k 2.2×	16	4.5k
Ronald Boellard Netherlands	4	3.8k 1.7×	265 0.3×	1.4k 1.9×	703 1.3×	1000 2.0×	4	4.2k
Ruben T. H. M. Larue Netherlands	12	4.0k 1.8×	329 0.4×	1.6k 2.1×	920 1.7×	1.1k 2.3×	14	4.6k
Sebastian Sanduleanu Netherlands	18	4.1k 1.9×	335 0.4×	1.6k 2.2×	899 1.6×	1.1k 2.3×	29	4.9k
Zelan Ma China	12	2.3k 1.0×	183 0.2×	1.1k 1.5×	795 1.4×	630 1.3×	18	2.8k
Charlotte Robert France	21	2.9k 1.3×	184 0.2×	1.4k 1.9×	866 1.6×	743 1.5×	59	3.8k

Countries citing papers authored by Jingwei Wei

Since Specialization

Citations

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

Fields of papers citing papers by Jingwei Wei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jingwei Wei

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

Wei, Jingwei, et al.. (2025). Evolving strategies in the diagnosis and treatment of HIV-associated neurocognitive disorders. Reviews in the Neurosciences. 36(6). 677–688. 1 indexed citations

Luo, Yang, Mengjie Fang, Shuo Wang, et al.. (2024). Multi-omics synergy in oncology: Unraveling the complex interplay of radiomic, genoproteomic, and pathological data. 1(1). 17–30. 3 indexed citations

Li, Yilin, Jiaojiao Liu, Jingwei Wei, et al.. (2024). Large scale models in radiology: revolutionizing the future of medical imaging. 3(1). 1 indexed citations

Wei, Jingwei, et al.. (2023). Radiomics: A radiological evidence-based artificial intelligence technique to facilitate personalized precision medicine in hepatocellular carcinoma. Digestive and Liver Disease. 55(7). 833–847. 15 indexed citations

Wei, Jingwei, Meng Niu, Yu Zhou, et al.. (2022). Advances in artificial intelligence techniques drive the application of radiomics in the clinical research of hepatocellular carcinoma. PubMed. 1(1). 49–54. 1 indexed citations

Wei, Jingwei, Yu Gao, Xiaozhen Yang, et al.. (2022). A multi‐scale, multi‐region and attention mechanism‐based deep learning framework for prediction of grading in hepatocellular carcinoma. Medical Physics. 50(4). 2290–2302. 13 indexed citations

Xu, Lu, Yuwei Zhang, Mu Zhou, et al.. (2021). Low-Dose CT Denoising Using A Structure-Preserving Kernel Prediction Network. 1639–1643. 4 indexed citations

Wei, Shengcai, Yuqi Han, Shuai Ye, et al.. (2021). Radiomics diagnosed histopathological growth pattern in prediction of response and 1-year progression free survival for colorectal liver metastases patients treated with bevacizumab containing chemotherapy. European Journal of Radiology. 142. 109863–109863. 17 indexed citations

Yang, Wanshui, Hanyu Jiang, Chao Liu, et al.. (2021). Multi-Omics and Its Clinical Application in Hepatocellular Carcinoma: Current Progress and Future Opportunities. Chinese Medical Sciences Journal. 36(3). 173–186. 2 indexed citations

10.

Dong, Di, Zhenchao Tang, Shuo Wang, et al.. (2020). The Role of Imaging in the Detection and Management of COVID-19: A Review. IEEE Reviews in Biomedical Engineering. 14. 16–29. 243 indexed citations

11.

Wang, Wentao, Dongsheng Gu, Jingwei Wei, et al.. (2020). A radiomics-based biomarker for cytokeratin 19 status of hepatocellular carcinoma with gadoxetic acid–enhanced MRI. European Radiology. 30(5). 3004–3014. 66 indexed citations

12.

Guo, Donghui, Dongsheng Gu, Honghai Wang, et al.. (2019). Radiomics analysis enables recurrence prediction for hepatocellular carcinoma after liver transplantation. European Journal of Radiology. 117. 33–40. 60 indexed citations

13.

Yuan, Chunwang, Zhenchang Wang, Dongsheng Gu, et al.. (2019). Prediction early recurrence of hepatocellular carcinoma eligible for curative ablation using a Radiomics nomogram. Cancer Imaging. 19(1). 21–21. 72 indexed citations

14.

Chen, Shuling, Shi‐Ting Feng, Jingwei Wei, et al.. (2019). Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging. European Radiology. 29(8). 4177–4187. 125 indexed citations

15.

Tian, Jie, Jingwei Wei, Sirui Fu, et al.. (2019). Development and validation of a radiomics-based method for macrovascular invasion prediction in hepatocellular carcinoma with prognostic implication. 34. 59–59.

16.

Tan, Yan, Shuaitong Zhang, Jingwei Wei, et al.. (2019). A radiomics nomogram may improve the prediction of IDH genotype for astrocytoma before surgery. European Radiology. 29(7). 3325–3337. 62 indexed citations

17.

Liu, Zhenyu, Shuo Wang, Di Dong, et al.. (2019). The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges. Theranostics. 9(5). 1303–1322. 658 indexed citations breakdown →

18.

Han, Yuqi, Yali Zang, Shuaitong Zhang, et al.. (2018). Non-invasive genotype prediction of chromosome 1p/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomas. Journal of Neuro-Oncology. 140(2). 297–306. 65 indexed citations

19.

Yang, Li, Dongsheng Gu, Jingwei Wei, et al.. (2018). A Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma. Liver Cancer. 8(5). 373–386. 241 indexed citations

20.

Wei, Jingwei, Guoqiang Yang, Xiaohan Hao, et al.. (2018). A multi-sequence and habitat-based MRI radiomics signature for preoperative prediction of MGMT promoter methylation in astrocytomas with prognostic implication. European Radiology. 29(2). 877–888. 104 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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