C. Wang

602 total citations
19 papers, 49 citations indexed

About

C. Wang is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Biomedical Engineering. According to data from OpenAlex, C. Wang has authored 19 papers receiving a total of 49 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Radiation and 4 papers in Biomedical Engineering. Recurrent topics in C. Wang's work include Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Imaging Techniques and Applications (5 papers) and Advanced Radiotherapy Techniques (4 papers). C. Wang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Imaging Techniques and Applications (5 papers) and Advanced Radiotherapy Techniques (4 papers). C. Wang collaborates with scholars based in United States, China and Saudi Arabia. C. Wang's co-authors include Scott D. Moore, W. A. Wilson, F Yin, John P. Kirkpatrick, Wenzheng Sun, Zheng Chang, Joshua N. Sampson, Yang Sheng, Miao Zhang and Boyan Gao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Neurophysiology and Journal of Agricultural and Food Chemistry.

In The Last Decade

C. Wang

15 papers receiving 49 citations

Peers

C. Wang
Santiago Candela‐Cantó Spain
Mattias Andréasson Sweden
Camillo Foresti Italy
Weiguo Tang China
A G Melikyan Russia
Hana Krijtová Czechia
Jonathan Rafael‐Patiño Switzerland
Yohan Davit France
Christopher Fugl Madelung Denmark
B. Guo China
Santiago Candela‐Cantó Spain
C. Wang
Citations per year, relative to C. Wang C. Wang (= 1×) peers Santiago Candela‐Cantó

Countries citing papers authored by C. Wang

Since Specialization
Citations

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

Fields of papers citing papers by C. Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of C. Wang

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

All Works

19 of 19 papers shown
1.
Chang, Yung‐Chun, et al.. (2025). Extracting critical clinical indicators and survival prediction of lung cancer from pathology reports using large language models. Computers in Biology and Medicine. 195. 110621–110621.
2.
3.
Wang, Yang, Yuanyuan Li, Changzhi Shi, et al.. (2025). Recent Advances in Nontargeted Screening of Chemical Hazards in Foodstuffs. Annual Review of Food Science and Technology. 16(1). 195–218.
4.
Zhu, Hanshu, Miao Zhang, Lin Zhu, et al.. (2025). Formation Patterns, In Vivo Toxic Effects, and Metabolomic Conditions of Oxidative Derivatives of Triolein. Journal of Agricultural and Food Chemistry. 73(32). 20421–20433.
5.
Zhang, Miao, C. Wang, Zhuohong Xie, Boyan Gao, & Liangli Yu. (2024). Chemical structures, analytical approaches and toxicological effects of oxidative derivatives of triglycerides as potential hazards in lipid thermal processing: A review. SHILAP Revista de lepidopterología. 7(4). 270–279. 3 indexed citations
6.
Wang, C., Hanshu Zhu, Miao Zhang, et al.. (2024). Ninety-Day Subchronic Toxicology of Individual and Combined Toxicants from the Thermal Processing of Lipid-Rich Foods. Journal of Agricultural and Food Chemistry. 72(50). 28122–28137. 1 indexed citations
7.
Sun, Junding, et al.. (2024). Mfpenet: multistage foreground-perception enhancement network for remote-sensing scene classification. The Visual Computer. 41(5). 3059–3076. 2 indexed citations
8.
Ni, Yuan, et al.. (2020). Automatic VMAT Planning via MLC Dynamic Sequence Prediction (AVP-DSP): A Novel Deep-Learning Method for Real-Time Prostate Treatment Planning. International Journal of Radiation Oncology*Biology*Physics. 108(3). S93–S94. 2 indexed citations
9.
Wang, C., Yang Sheng, Manisha Palta, et al.. (2020). Simulating Planners’ Interactions With the Treatment Planning System: A Reinforcement Learning Study for Pancreas SBRT Planning. International Journal of Radiation Oncology*Biology*Physics. 108(3). e255–e256. 1 indexed citations
10.
Sheng, Yang, et al.. (2020). Quantifying the Progression of Clinical Knowledge with a Knowledge-based Tradeoff Model. International Journal of Radiation Oncology*Biology*Physics. 108(3). S94–S95. 1 indexed citations
11.
Wang, C., et al.. (2019). Rapid Auto IMRT Planning Using Cascade Dense Convolutional Neural Network (CDCNN): A Feasibility Study for Fluence Map Prediction Using Deep Learning on Prostate IMRT Patients. International Journal of Radiation Oncology*Biology*Physics. 105(1). E789–E790. 1 indexed citations
12.
Vergalasova, Irina, C. Wang, Yang Sheng, et al.. (2019). Significant Inter-Planner Variability in Plan Quality for VMAT-Based Multi-Target Stereotactic Radiosurgery (SRS): A Multi-Institution Analysis. International Journal of Radiation Oncology*Biology*Physics. 105(1). E767–E767. 1 indexed citations
13.
Wang, C., Kyle J. Lafata, Yushi Chang, et al.. (2019). Dose-Distribution-Driven PET Image-based Outcome Prediction (DDD-PIOP): A Framework Design for Oropharyngeal Cancer IMRT Application. International Journal of Radiation Oncology*Biology*Physics. 105(1). S81–S82. 1 indexed citations
14.
Wu, Qiuwen, Oana Craciunescu, Anna Rodrigues, et al.. (2018). Commissioning and Clinical Implementation of a Laying Down Technique for Total Skin Irradiation. International Journal of Radiation Oncology*Biology*Physics. 102(3). e480–e480. 1 indexed citations
15.
Wang, C., Wenzheng Sun, John P. Kirkpatrick, et al.. (2017). Assessment of Concurrent Stereotactic Radiosurgery and Bevacizumab Treatment of Recurrent Malignant Gliomas Using Multiparametric MRI Imaging and Radiomics Analysis. International Journal of Radiation Oncology*Biology*Physics. 99(2). E734–E734. 12 indexed citations
16.
Lafata, Kyle J., et al.. (2017). Sensitivity of Radiomic Features to Acquisition Noise and Respiratory Motion. International Journal of Radiation Oncology*Biology*Physics. 99(2). S93–S94. 1 indexed citations
17.
Yin, F, C. Wang, Chang Zhang, et al.. (2016). Ultrafast Volumetric Cine Magnetic Resonance Imaging (UVC-MRI) for Real-Time 3-Dimensional Target Localization/Tracking. International Journal of Radiation Oncology*Biology*Physics. 96(2). E626–E626. 1 indexed citations
18.
Wang, C., Janet K. Horton, F Yin, & Zheng Chang. (2015). Treatment Assessment Using Dynamic Fractal Signature Dissimilarity as a Novel Biomarker for Early-Stage Breast Cancer Radiation Therapy: A Feasibility Study. International Journal of Radiation Oncology*Biology*Physics. 93(3). S5–S5. 1 indexed citations
19.
Wang, C., W. A. Wilson, & Scott D. Moore. (2001). Role of NMDA, Non-NMDA, and GABA Receptors in Signal Propagation in the Amygdala Formation. Journal of Neurophysiology. 86(3). 1422–1429. 20 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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