代表性成果 (论文/专利/专著等) |
代表论文: 1. Cui Y#, Zhao K#, Meng X#, Mao Y#, Han C, Shi Zh, Yang X*(杨晓棠), Tong T*, Wu L *, Liu Z*. A CT-based multitask deep learning model for predicting tumor stroma ratio and treatment outcomes in patients with colorectal cancer: a multicenter cohort study. International Journal of Surgery. 2024 May 1;110(5):2845-2854. 2. Zheng Y#, Qiu B#,, Liu S#,, Song R#,, Yang X, Wu L, Chen Z, Tuersun A, Yang X*(杨晓棠), Wang W*, Liu Z*. A transformer-based deep learning model for early prediction of lymph node metastasis in locally advanced gastric cancer after neoadjuvant chemotherapy using pretreatment CT images. EClinicalMedicine. 2024 Aug 30;75:102805. 3. Rian Huang, Zeyan Xu, Yu Xie, Hong Wu, Zixian Li, Yanfen Cui, Yingwen Huo, Chu Han, Xiaotang Yang∗(杨晓棠), Zaiyi Liu, Yi Wang. Joint-phase attention network for breast cancer segmentation in DCE-MRI. Expert Systems With Applications. Volume 224, 15 August 2023, 119962. 4. Cui Y#, Zhang J#, Li Zh#, Wei K#, Ye Lei, Ren J, Wu L, Shi Zh, Meng X*, Yang X*(杨晓棠), Gao X*. A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: a multicenter cohort study. EclinicalMedicine. 2022, 46: 101348. 5. Zhang J#, Cui Y#, Wei K#, Li Zh#, Li D, Song R, Ren J, Gao X, Yang X*(杨晓棠). Deep Learning Predicts Resistance to Neoadjuvant Chemotherapy for Locally Advanced Gastric Cancer: A Multicenter Study.Gastric cancer.2022;25(6):1050-9. 6. Song R#, Cui Y#, Ren J, Zhang J, Yang Z, Li D, Li Z*, Yang X* Yang X*(杨晓棠). CT-based radiomics analysis in the prediction of response to neoadjuvant chemotherapy in locally advanced gastric cancer: A dual-center study. Radiotherapy and Oncology 2022, 171: 155-163. 7. Cui Y#, Yang W#, Ren J, Li D, Zhang J, Yang X*(杨晓棠). Prognostic value of multiparametric MRI-based radiomics model: Potential role for chemotherapeutic benefits in locally advanced rectal cancer. Radiotherapy and Oncology 2021, 154: 161-169. 8. Cui Y#, Liu H#, Ren J, Du X, Xin L, Li D, Yang X*(杨晓棠), Wang D*. Development and Validation of a MRI-Based Radiomics Signature for Prediction of KRAS mutation in rectal Cancer. European Radiology 2020 Apr;30(4): 1948-1958. 9. Zhang J#, Wang G#, Ren J, Yang Z, MD, Li D, Cui Y*, Yang X*(杨晓棠). Multiparametric MRI-based radiomics nomogram for preoperative prediction of lymphovascular invasion and clinical outcomes in patients with breast invasive ductal carcinoma. European radiology 2022, 32: 4079-4089. 10. Cui Y#, Wang G#, Ren J, Hou L, Li D, Wen Q, Xi Y*, Yang X*(杨晓棠). Radiomics Features at Multiparametric MRI Predict Disease-Free Survival in Patients With Locally Advanced Rectal Cancer. Academic Radiology, 2022 08;29(8). 11. Li D#*, Chu X, Cui Y#, Zhao J, Zhang K, Yang X#(杨晓棠). Improved U-Net based on contour prediction for efficient segmentation of rectal cancer. Comput Methods Programs Biomed, 2022 Jan;213:106493. (2021 IF=7.027) 12. Cui Y#, Yang W#, Ren J, Li D, Zhang J, Yang X*(杨晓棠).Prognostic value of multiparametric MRI-based radiomics model: Potential role for chemotherapeutic benefits in locally advanced rectal cancer. Radiother Oncol, 2021, 154: 161-169. 13. Yang W#, Dong Y, Du Q, Qiang Y, Wu K , Zhao J∗, Yang X∗(杨晓棠) , M.Bilal Zia. Integrate domain knowledge in training multi-task cascade deep learning model for benign–malignant thyroid nodule classification on ultrasound images. Engineerig Applicatioses of Artificial Intelligenc. 2021, 98, 104064. 14. Dong Y#, Hou L#, Yang W, J Han, Wang J, Qiang Y*, Zhao J, Hou J , Song K, Ma Y, N.G.F .Kazihise, Cui Y, Yang X*(杨晓棠). Multi-channel multi-task deep learning for predicting EGFR and KRAS mutations of non-small cell lung cancer on CT images. Quantitative imaging in medicine and surgery. 2021, 11 (6), 2354-2375. 15. Li H#, Xue R#, Yang X*(杨晓棠), Han S, Yang W, Song X, Zhang X, Cao J, Jia S, Wang W, Lian J. Best Supportive Care Versus Whole-Brain Irradiation, Chemotherapy Alone, or WBRT Plus Chemotherapy in Patients With Brain Metastases From Small-Cell Lung Cancer: A Case-Controlled Analysis. Front Oncol. 2021, 11, 568568. 专著: 1. 脊柱影像学. 化学工业出版社医学出版分社,2007,5 2. 胃肠道间质瘤影像诊断. 人民卫生出版社,2009,5 3. 动态定量磁共振成像. 人民卫生出版社,2018.10 4. 中华医学影像案例解析宝典 乳腺分册,人民卫生出版社,2018.04,编委 |