代表性成果 （论文/专利/专著等） |
1. Lingjie Wang, Tiedan Guo, Li Wang, et al. Improving radiomic modeling for the identification of symptomatic carotid atherosclerotic plaques using deep learning-based 3D super-resolution CT angiography[J]. Heliyon, 2024,10(8):e29331. DOI: 10.1016/j.heliyon.2024.e29331. 2. Lingjie Wang, Xiaoqian Zhang, Hongrong Zhang, et al. Novel Metal-Free Nanozyme for Targeted Imaging and Inhibition of Atherosclerosis via Macrophage Autophagy Activation to Prevent Vulnerable Plaque Formation and Rupture[J]. ACS Appl. Mater. Interfaces, 2024, DOI:https://doi.org/10.1021/acsami.4c08671. 3. Fanxiu Meng, Jianxin Zhang, Lingjie Wang, et al. Contrast-Enhanced CT-Based Deep Learning Radiomics Nomogram for the Survival Prediction in Gallbladder Cancer[J]. ACADEMIC RADIOLOGY, 2024,31(6):2356-2366. 4. Lingjie Wang, Peiqing Zhai, Lili Xue, et al. Machine learning-based identification of symptomatic carotid atherosclerotic plaques with dual-energy computed tomography angiography[J]. J Stroke Cerebrovasc Dis, 2023,32(8):107209. DOI: 10.1016/j.jstrokecerebrovasdis.2023.107209. 5. 石彩云,王灵杰,张华.基于巨噬细胞的动脉粥样硬化易损斑块靶向成像的研究进展[J].中华核医学与分子影像杂志, 2022, 42(8):499-503. DOI:10.3760/cma.j.cn321828-20210103-00002. 6. 薛丽丽,王灵杰,石彩云,等.颅内外动脉并存粥样硬化斑块的研究进展[J].实用心脑肺血管病杂志,2023,31(2):130-134.DOI:10.12114/j.issn.1008-5971.2023.00.006. 7. 薛丽丽,王灵杰,石彩云,等.CTA识别症状性颈动脉斑块的放射组学研究[J].中西医结合心脑血管病杂志,2023, 21(11):2083-2088. DOI:10.12102/j.issn.1672-1349.2023.11.032. 8. 郭铁旦,王灵杰,石彩云,等.颈动脉全斑块自动分割的影像组学模型对缺血性脑卒中的预测价值[J].中西医结合心脑血管病杂志, 2024, 22(12):2269-2275. DOI:10.12102/j.issn.1672-1349.2024.12.031. 9. 翟沛清,王灵杰,石彩云,等.整合能谱CT定量参数的机器学习模型对症状性颈动脉斑块识别的应用研究[J].临床放射学杂志, 2024, 43(1):22-28. DOI:10.13437/j.cnki.jcr.2024.01.020. |
