Kexue Deng

533 total citations
29 papers, 302 citations indexed

About

Kexue Deng is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Biomedical Engineering. According to data from OpenAlex, Kexue Deng has authored 29 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Pulmonary and Respiratory Medicine and 5 papers in Biomedical Engineering. Recurrent topics in Kexue Deng's work include Radiomics and Machine Learning in Medical Imaging (17 papers), COVID-19 diagnosis using AI (7 papers) and MRI in cancer diagnosis (6 papers). Kexue Deng is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (17 papers), COVID-19 diagnosis using AI (7 papers) and MRI in cancer diagnosis (6 papers). Kexue Deng collaborates with scholars based in China, United States and Hong Kong. Kexue Deng's co-authors include Jiangdian Song, Kristen W. Yeom, Hongmei Wang, Lu Wang, Jimmy Zheng, Safwan S. Halabi, Edward H. Lee, Wei Zhang, Chunlei Liu and Wei Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nanoscale and Acta Neuropathologica.

In The Last Decade

Kexue Deng

27 papers receiving 299 citations

Peers

Kexue Deng

RNMI

PRM

René Hosch Germany

Zhuangsheng Liu China

Philipp Fervers Germany

Sohee Park South Korea

Tobias Hepp Germany

Naziya Samreen United States

Beibei Jiang China

Carsten Ammitzbøl Lauridsen Denmark

Koichiro Kimura Japan

Christian V. Guthier United States

René Hosch Germany

Kexue Deng

157 ×0.7

RNMI

48 ×0.6

PRM

43 ×0.7

58 ×1.0

42 ×0.9

Citations per year, relative to Kexue Deng Kexue Deng (= 1×) peers René Hosch

Countries citing papers authored by Kexue Deng

Since Specialization

Citations

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

Fields of papers citing papers by Kexue Deng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kexue Deng

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

Xu, Nan‐Jie, Jiajun Wang, Tao Lu, et al.. (2024). EfficientNet-Based System for Detecting EGFR-Mutant Status and Predicting Prognosis of Tyrosine Kinase Inhibitors in Patients with NSCLC. Journal of Imaging Informatics in Medicine. 37(3). 1086–1099. 2 indexed citations

Wang, Jiajun, et al.. (2024). Assessing the reproducibility, stability, and biological interpretability of multimodal computed tomography image features for prognosis in advanced non‐small cell lung cancer. SHILAP Revista de lepidopterología. 2(1). 3–16.

Deng, Kexue, et al.. (2024). Based on Gadolinium Ethoxybenzyl DTPA–Enhanced MRI: Diagnostic Performance of the Category-Modified LR-5 Criteria in Patients At Risk for Hepatocellular Carcinoma. Technology in Cancer Research & Treatment. 23. 2233998747–2233998747. 1 indexed citations

Chen, Chuan‐Yu, et al.. (2024). A vision transformer‐based deep transfer learning nomogram for predicting lymph node metastasis in lung adenocarcinoma. Medical Physics. 52(1). 375–387. 3 indexed citations

Song, Xiaopeng, et al.. (2024). Comparison of single shot and multishot diffusion-weighted imaging in 5-T magnetic resonance imaging for brain disease diagnosis. Quantitative Imaging in Medicine and Surgery. 14(10). 7291–7305. 1 indexed citations

Wang, Lu, Nan‐Jie Xu, Xiran Jiang, et al.. (2023). A general approach for automatic segmentation of pneumonia, pulmonary nodule, and tuberculosis in CT images. iScience. 26(7). 107005–107005. 7 indexed citations

Zhang, Yong, et al.. (2023). Investigation of brain iron levels in Chinese patients with Alzheimer’s disease. Frontiers in Aging Neuroscience. 15. 1168845–1168845. 4 indexed citations

Hu, Yue, Tao Jiang, Jiangdian Song, et al.. (2023). Ct-based subregional radiomics using hand-crafted and deep learning features for prediction of therapeutic response to anti-PD1 therapy in NSCLC. Physica Medica. 117. 103200–103200. 4 indexed citations

Zhang, Qiong, Tao Zhang, Fei Ling, et al.. (2023). A Case of Giant Left Circumflex Coronary Fistula Aneurysm with Unidentified Fistula. International Heart Journal. 64(4). 775–778. 1 indexed citations

10.

Li, Shaopeng, Peng Wang, & Kexue Deng. (2022). Imaging presentation of biliary adenofibroma: A case report. World Journal of Clinical Cases. 10(4). 1366–1372. 4 indexed citations

11.

Wang, Hwa‐Chain Robert, Nan Xu, Yuanyuan Sun, et al.. (2022). Development and validation of a deep learning model for survival prognosis of transcatheter arterial chemoembolization in patients with intermediate-stage hepatocellular carcinoma. European Journal of Radiology. 156. 110527–110527. 22 indexed citations

12.

Song, Jiangdian, et al.. (2021). Correction to: End-to-end automatic differentiation of the coronavirus disease 2019 (COVID-19) from viral pneumonia based on chest CT. European Journal of Nuclear Medicine and Molecular Imaging. 48(5). 1698–1698. 1 indexed citations

13.

Wang, Hongmei, Lu Wang, Edward H. Lee, et al.. (2021). Correction to: Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures. European Journal of Nuclear Medicine and Molecular Imaging. 48(5). 1697–1697. 1 indexed citations

14.

Wang, Lu, Edward H. Lee, Hongmei Wang, et al.. (2021). Multi-classifier-based identification of COVID-19 from chest computed tomography using generalizable and interpretable radiomics features. European Journal of Radiology. 136. 109552–109552. 23 indexed citations

15.

Qiu, Jun, Kexue Deng, Peng Wang, et al.. (2021). Application of diffusion kurtosis imaging to the study of edema in solid and peritumoral areas of glioma. Magnetic Resonance Imaging. 86. 10–16. 11 indexed citations

16.

Wang, Hongmei, Lu Wang, Edward H. Lee, et al.. (2020). Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures. European Journal of Nuclear Medicine and Molecular Imaging. 48(5). 1478–1486. 74 indexed citations

17.

Song, Jiangdian, et al.. (2020). End-to-end automatic differentiation of the coronavirus disease 2019 (COVID-19) from viral pneumonia based on chest CT. European Journal of Nuclear Medicine and Molecular Imaging. 47(11). 2516–2524. 59 indexed citations

18.

Liu, Gang, Lin Kong, Hongping Zhou, et al.. (2020). Multifunctional BaMnLuGdF7: Yb/Er/Ho nanoparticles for in vivo tri-modal imaging. Optical Materials. 111. 110578–110578. 4 indexed citations

19.

Dong, Lu, Wei‐Fu Lv, Ming Ni, et al.. (2016). Diagnostic value of multislice computerized tomography angiography for aortic dissection: A comparison with DSA. Experimental and Therapeutic Medicine. 13(2). 405–412. 6 indexed citations

20.

Wei, Wei, et al.. (2014). Predictive value of dual-energy spectral computed tomographic imaging on the histological origin of carcinomas in the ampullary region. Abdominal Imaging. 39(4). 702–710. 4 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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