1.  Di Dong#, Mengjie Fang#, Lei Tang#, Xiuhong Shan#, Jianbo Gao#, Francesco Giganti#, Rongpin Wang, Xin Chen, Xiaoxiao Wang, Diego Palumbo, Jia Fu, Wuchao Li, Jing Li, Lianzhen Zhong, Francesco De Cobelli, Jiafu Ji*, Zaiyi Liu*, Jie Tian*, Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study, Annals of Oncology, 2020, 31(7): 912-920. Published: April 15, 2020. DOI: 10.1016/j.annonc.2020.04.003.

2.  Huang Y, Liang C, He L, et al. Development and validation of a radiomics nomogram for preoperative prediction of lymph node metastasis in colorectal cancer[J]. Journal of Clinical Oncology, 2016, 34(18): 2157-2164.

3.  Di Dong, Lei Tang, Ziyu Li, Mengjie Fang, Jianbo Gao, Xiuhong Shan et al. Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer, Annals of Oncology, 2019, 30(3): 431-438.

4.  Di Dong#, Fan Zhang#, Lianzhen Zhong#, Mengjie Fang, Chenglong Huang, Jijin Yao, Ying Sun, Jie Tian*, Jun Ma*, Linglong Tang*, Development and validation of a novel MR imaging predictor of response to induction chemotherapy in locoregionally advanced nasopharyngeal cancer: a randomized controlled trial substudy (NCT01245959), BMC Medicine, 2019, 17(1): 190. Published: October 23, 2019. DOI: 10.1186/s12916-019-1422-6.

5.  Di Dong#, Zhenchao Tang#, Shuo Wang#, Hui Hui#, Lixin Gong#, Yao Lu#, Zhong Xue, Hongen Liao, Fang Chen, Fan Yang, Ronghua Jin, Kun Wang, Zhenyu Liu, Jingwei Wei, Wei Mu, Hui Zhang, Jingying Jiang, Jie Tian*, Hongjun Li*, The role of imaging in the detection and management of COVID-19: a review, IEEE Reviews in Biomedical Engineering, 2020,14:16-29. Published: 27 April 2020. DOI: 10.1109/RBME.2020.2990.

6.  Wang K, Lu X, Zhou H, Tian J, et al. Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study.[J]. Gut. 2018 May: doi:10.1136/gutjnl-2018-316204. PMID: 29730602.

7.  Shuo Wang, Jingyun Shi, Zhaoxiang Ye, Di Dong, Dongdong Yu, Mu Zhou. et al. Predicting EGFR Mutation Status in Lung Adenocarcinoma on CT Image Using Deep Learning, European Respiratory Journal, 2019, 53 (3): 1800986.

8.  Hao Peng, Di Dong, Mengjie Fang, Lu Li, Linglong Tang, et al, Prognostic Value of Deep Learning PET/CT-based Radiomics: Potential Role for Future Individual Induction Chemotherapy in Advanced Nasopharyngeal Carcinoma, Clinical Cancer Research, 2019. DOI:10.1158/1078-0432.CCR-18-3065 .

9.  Jiangdian Song, Jingyun Shi, Di Dong, Mengjie Fang, et al. A new approach to predict progression-free survival in stage IV EGFR-mutant NSCLC patients with EGFR-TKI therapy, Clinical Cancer Research, 2018, 24(15): 3583-3592.

10.  Bin Zhang#, Jie Tian#, Di Dong#, Dongsheng Gu, Yuhao Dong, Lu Zhang, Zhouyang Lian, Jing Liu, Xiaoning Luo, Shufang Pei, Xiaokai Mo, Wenhui Huang, Fusheng Ouyang, Baoliang Guo, Long Liang, Wenbo Chen, Changhong Liang, Shuixing Zhang*, Radiomics features of multiparametric MRI as novel prognostic factors in advanced nasopharyngeal carcinoma, Clinical Cancer Research, 2017, 23(15): 4259-4269. Published: August 2017. DOI: 10.1158/1078-0432.CCR-16-2910.

11.  Yujia Liu#, Hui Duan#, Di Dong#, Jiaming Chen#, Lianzhen Zhong, Liwen Zhang, Runnan Cao, Huijian Fan, Zhumei Cui, Ping Liu, Shan Kang, Xuemei Zhan, Shaoguang Wang, Xun Zhao, Chunlin Chen*, Jie Tian*, Development of a deep learning-based nomogram for predicting lymph node metastasis in cervical cancer: a multicenter study, Clinical and Translational Medicine, 2022,12: e938. First published: 15 July 2022. DOI: 10.1002/ctm2.938.

12.  Shuo Wang#, Mu Zhou#, Zaiyi Liu, Zhenyu Liu, Dongsheng Gu, Yali Zang, Di Dong#, Olivier Gevaert#, Jie Tian*, Central focused convolutional neural networks: developing a data-driven model for lung nodule segmentation, Medical Image Analysis, 2017, 40: 172–183. Published: August 2017. DOI: 10.1016/j.media.2017.06.014.

13.  Bingxi He#, Di Dong#, Yunlang She#, Caicun Zhou, Mengjie Fang, Yongbei Zhu, Henghui Zhang, Zhipei Huang*, Tao Jiang*, Jie Tian*, Chang Chen*, Predicting response to immunotherapy in advanced non-small cell lung cancer using tumour mutational burden radiomic biomarker, Journal for ImmunoTherapy of Cancer, 2020, 8(2): e000550. Published: July 6, 2020. DOI: 10.1136/jitc-2020-000550.

14.  Panwen Tian#, Bingxi He#, Wei Mu#, Kunqin Liu, Li Liu, Hao Zeng, Yujie Liu, Lili Jiang, Ping Zhou, Zhipei Huang*, Di Dong*, Weimin Li*, Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images, Theranostics, 2021, 11(5): 2098-2107. Published: 2021-1-1. doi: 10.7150/thno.48027.

15.  Zhenyu Liu#, Shuo Wang#, Di Dong#, Jingwei Wei#, Cheng Fang#, Xuezhi Zhou, Kai Sun, Longfei Li, Bo Li*, Meiyun Wang*, Jie Tian*, The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges, Theranostics, 2019, 9(5): 1303–1322. Published: 2019-2-12. DOI: 10.7150/thno.30309.

16.  Hao Hu#, Lixin Gong#, Di Dong#, Liang Zhu, Min Wang, Jie He, Lei Shu, Yiling Cai, Shilun Cai, Wei Su, Yunshi Zhong, Cong Li, Yongbei Zhu, Mengjie Fang, Lianzhen Zhong, Xin Yang, Pinghong Zhou*, Jie Tian*, Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study, Gastrointestinal Endoscopy, 2021, 93(6): 1333-1341.e3. Published: November 25, 2020. DOI: 10.1016/j.gie.2020.11.014.

17.  Xun Zhao#, Yujing Liang#, Xu Zhang#, Dongxiang Wen#, Wei Fan#, Linquan Tang*, Di Dong*, Jie Tian*, Haiqiang Mai*, Deep learning signatures reveal multiscale intratumor heterogeneity associated with biological functions and survival in recurrent nasopharyngeal carcinoma, European Journal of Nuclear Medicine and Molecular Imaging, 2022, 49: 2972–2982. Published online: 26 April 2022. DOI: 10.1007/s00259-022-05793-x.

18.  Liwen Zhang#, Di Dong#, Yongqing Sun#, Chaoen Hu, Congxin Sun#, Qingqing Wu*, Jie Tian*, Development and validation of a deep learning model to screen for trisomy 21 during the first trimester from nuchal ultrasonographic images, JAMA Network Open, 2022, 5(6): e2217854. Published: June 21, 2022. DOI: 10.1001/jamanetworkopen.2022.17854.

19.  Liwen Zhang#, Lianzhen Zhong#, Cong Li, Wenjuan Zhang, Chaoen Hu, Di Dong*, Zaiyi Liu*, Junlin Zhou*, Jie Tian*, Knowledge-guided multi-task attention network for survival risk prediction using multi-center computed tomography images, Neural Networks, 152: 394-406. Available online 28 April 2022. DOI: 10.1016/j.neunet.2022.04.027.

20.  Fan Zhang#, Lianzhen Zhong#, Xun Zhao#, Di Dong#, Jijin Yao, Siyang Wang, Ye Liu, Ding Zhu, Yin Wang, Guojie Wang, Yiming Wang, Dan Li, Jiang Wei*, Jie Tian*, Hong Shan*, A deep-learning-based prognostic nomogram integrating microscopic digital pathology and macroscopic magnetic resonance images in nasopharyngeal carcinoma: a multi-cohort study, Therapeutic Advances in Medical Oncology, 2020, 12: 1-12.