Jiancong Wang

763 total citations
24 papers, 414 citations indexed

About

Jiancong Wang is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Jiancong Wang has authored 24 papers receiving a total of 414 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 8 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Biomedical Engineering. Recurrent topics in Jiancong Wang's work include Radiomics and Machine Learning in Medical Imaging (4 papers), Dementia and Cognitive Impairment Research (4 papers) and Pregnancy and preeclampsia studies (3 papers). Jiancong Wang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), Dementia and Cognitive Impairment Research (4 papers) and Pregnancy and preeclampsia studies (3 papers). Jiancong Wang collaborates with scholars based in United States, China and Sweden. Jiancong Wang's co-authors include James C. Gee, Long Xie, Jeffrey D. Rudie, Andreas M. Rauschecker, Suyash Mohan, Michael Tran Duong, Paul A. Yushkevich, Jianbo Shi, Yuhua Chen and Yifan Wu and has published in prestigious journals such as NeuroImage, Radiology and Frontiers in Plant Science.

In The Last Decade

Jiancong Wang

22 papers receiving 402 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiancong Wang United States 12 175 157 97 75 70 24 414
Dzhoshkun I. Shakir United Kingdom 9 221 1.3× 160 1.0× 131 1.4× 60 0.8× 105 1.5× 22 532
Han Zhou China 9 98 0.6× 115 0.7× 113 1.2× 28 0.4× 38 0.5× 37 378
Lucas Fidon United Kingdom 6 216 1.2× 138 0.9× 131 1.4× 60 0.8× 84 1.2× 13 447
Maria Inês Meyer Belgium 5 220 1.3× 177 1.1× 88 0.9× 25 0.3× 42 0.6× 5 368
April Khademi Canada 14 232 1.3× 173 1.1× 134 1.4× 99 1.3× 35 0.5× 48 525
Zhuoyuan Li China 6 121 0.7× 89 0.6× 101 1.0× 54 0.7× 34 0.5× 12 301
Kaisar Kushibar Spain 11 200 1.1× 143 0.9× 210 2.2× 89 1.2× 39 0.6× 16 497
Polyxeni Gkontra Spain 14 240 1.4× 63 0.4× 157 1.6× 40 0.5× 102 1.5× 31 616
Ivan Coronado United States 8 145 0.8× 84 0.5× 56 0.6× 98 1.3× 58 0.8× 12 330
Mingquan Lin United States 11 163 0.9× 102 0.6× 117 1.2× 35 0.5× 32 0.5× 48 397

Countries citing papers authored by Jiancong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jiancong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiancong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Jiancong Wang. A scholar is included among the top collaborators of Jiancong 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 Jiancong Wang. Jiancong Wang 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.
2.
Wei, Xinran, et al.. (2025). Renewable energy consumption in Mercosur region: The role of human resources and green innovative technology. Energy Strategy Reviews. 58. 101662–101662. 1 indexed citations
3.
Tan, Zhiping, Dapeng Ye, Jiancong Wang, & Wenxiang Wang. (2025). P4CN-YOLOv5s: a passion fruit pests detection method based on lightweight-improved YOLOv5s. Frontiers in Plant Science. 16. 1612642–1612642. 2 indexed citations
4.
Zhang, Liyuan, et al.. (2024). Economic policy uncertainty and corporate green innovation. International Review of Financial Analysis. 97. 103797–103797. 11 indexed citations
5.
Wisse, Laura E.M., Robin de Florès, Jiancong Wang, et al.. (2023). Comparison of Focal Hippocampal T2‐Weighted MRI and Whole‐Brain T1‐Weighted MRI for Detection of Longitudinal Atrophy Using Deep Learning‐Based and Conventional Approaches. Alzheimer s & Dementia. 19(S24). 1 indexed citations
6.
Lyu, Xueying, Pulkit Khandelwal, Michael Tran Duong, et al.. (2023). tau‐neurodegeneration mismatch from inter‐modality image translation using deep learning. Alzheimer s & Dementia. 19(S10).
7.
Wang, Jiancong, et al.. (2022). NODEO: A Neural Ordinary Differential Equation Based Optimization Framework for Deformable Image Registration. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 20772–20781. 14 indexed citations
8.
Schwartz, Nadav, İpek Oğuz, Jiancong Wang, et al.. (2022). Fully Automated Placental Volume Quantification From 3D Ultrasound for Prediction of Small-for-Gestational-Age Infants. Obstetrical & Gynecological Survey. 77(12). 713–715. 1 indexed citations
9.
Xie, Long, Sandhitsu R. Das, Jiancong Wang, et al.. (2021). DeepAtrophy: Teaching a neural network to detect progressive changes in longitudinal MRI of the hippocampal region in Alzheimer's disease. NeuroImage. 243. 118514–118514. 12 indexed citations
10.
Schwartz, Nadav, İpek Oğuz, Jiancong Wang, et al.. (2021). Fully Automated Placental Volume Quantification From3DUltrasound for Prediction of Small‐for‐Gestational‐Age Infants. Journal of Ultrasound in Medicine. 41(6). 1509–1524. 6 indexed citations
11.
Rauschecker, Andreas M., Jeffrey D. Rudie, Long Xie, et al.. (2020). Artificial Intelligence System Approaching Neuroradiologist-level Differential Diagnosis Accuracy at Brain MRI. Radiology. 295(3). 626–637. 87 indexed citations
12.
Wang, Jiancong, Yuhua Chen, Yifan Wu, Jianbo Shi, & James C. Gee. (2020). Enhanced generative adversarial network for 3D brain MRI super-resolution. 3616–3625. 46 indexed citations
13.
Rudie, Jeffrey D., Andreas M. Rauschecker, Long Xie, et al.. (2020). Subspecialty-Level Deep Gray Matter Differential Diagnoses with Deep Learning and Bayesian Networks on Clinical Brain MRI: A Pilot Study. Radiology Artificial Intelligence. 2(5). e190146–e190146. 22 indexed citations
14.
Zhang, Lingzhi, Jiancong Wang, & Jianbo Shi. (2020). Multimodal Image Outpainting with Regularized Normalized Diversification. 3422–3431. 11 indexed citations
15.
16.
Duong, Michael Tran, Jeffrey D. Rudie, Jiancong Wang, et al.. (2019). Convolutional Neural Network for Automated FLAIR Lesion Segmentation on Clinical Brain MR Imaging. American Journal of Neuroradiology. 40(8). 1282–1290. 56 indexed citations
17.
Guo, Yumeng, Fu-Lai Chung, Guozheng Li, Jiancong Wang, & James C. Gee. (2019). Leveraging Label-Specific Discriminant Mapping Features for Multi-Label Learning. ACM Transactions on Knowledge Discovery from Data. 13(2). 1–23. 29 indexed citations
18.
Rudie, Jeffrey D., David Weiß, Andreas M. Rauschecker, et al.. (2019). Multi-Disease Segmentation of Gliomas and White Matter Hyperintensities in the BraTS Data Using a 3D Convolutional Neural Network. Frontiers in Computational Neuroscience. 13. 84–84. 30 indexed citations
19.
Xie, Long, Laura E.M. Wisse, Sandhitsu R. Das, et al.. (2018). Characterizing Anatomical Variability and Alzheimer’s Disease Related Cortical Thinning in the Medial Temporal Lobe Using Graph-Based Groupwise Registration and Point Set Geodesic Shooting. Lecture notes in computer science. 11167. 28–37. 6 indexed citations
20.
Chen, Min, Jiancong Wang, İpek Oğuz, Brian L. VanderBeek, & James C. Gee. (2017). Automated Segmentation of the Choroid in EDI-OCT Images with Retinal Pathology Using Convolution Neural Networks. Lecture notes in computer science. 10554. 177–184. 29 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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