21.  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.

22.  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.

23.  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.

24.  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.

25.  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.

26.  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.

27.  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.

28.  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.

29.  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.

30.  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.

31.  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.

32.  Runnan Cao#, Lixin Gong#, Di Dong*, Pathological diagnosis and prognosis of gastric cancer through a multi-instance learning method. EbioMedicine, 2021, 73: 103671, Published: October 27, 2021. DOI: 10.1016/j.ebiom.2021.103671.

33.  Lianzhen Zhong#, Di Dong#, Xueliang Fang#, Fan Zhang#, Ning Zhang#, Liwen Zhang#, Mengjie Fang, Wei Jiang, Shaobo Liang, Cong Li, Yujia Liu, Xun Zhao, Runnan Cao, Hong Shan, Zhenhua Hu*, Jun Ma*, Linglong Tang*, Jie Tian*. A deep learning-based radiomic nomogram for prognosis and treatment decision in advanced nasopharyngeal carcinoma: a multicentre study. EbioMedicine, 2021, 70: 103522. Available online 11 August 2021. DOI: 10.1016/j.ebiom.2021.103522.

34.  Lu Zhang#, Di Dong#, Hailin Li#, Jie Tian#, Fusheng Ouyang, Xiaokai Mo, Bin Zhang, Xiaoning Luo, Zhouyang Lian, Shufang Pei, Yuhao Dong, Wenhui Huang, Changhong Liang, Jing Liu*, Shuixing Zhang*, Development and validation of a magnetic resonance imaging-based model for the prediction of distant metastasis before initial treatment of nasopharyngeal carcinoma: a retrospective cohort study, EBioMedicine, 2019, 40: 327-335. Published: January 11, 2019. DOI: 10.1016/j.ebiom.2019.01.013.

35.  Yongqing Sun#, Liwen Zhang#, Di Dong#, Xiaofei Li, Jingjing Wang, Chenghong Yin*, Liona C. Poon*, Jie Tian*, Qingqing Wu*, Application of an individualized nomogram in first-trimester screening for trisomy 21, Ultrasound in Obstetrics and Gynecology, 2021, 58(1): 56-66. Issue Online:01 July 2021. DOI: 10.1002/uog.22087.

36.  Bingxi He#, Yifan Zhong#, Yongbei Zhu#, Jiajun Deng, Mengjie Fang, Yunlang She, Tingting Wang, Yang Yang, Xiwen Sun, Lorenzo Belluomini, Satoshi Watanabe, Di Dong*, Jie Tian*, Dong Xie*, Deep learning for predicting immunotherapeutic efficacy in advanced non-small cell lung cancer patients: a retrospective study combining progression-free survival risk and overall survival risk, Translational Lung Cancer Research, 2022, 11(4):670-685. Published: April 2022. DOI: 10.21037/tlcr-22-244.

37.  Liwen Zhang#, Di Dong#, Lianzhen Zhong#, Cong Li, Chaoen Hu, Xin Yang, Zaiyi Liu*, Rongpin Wang*, Junlin Zhou*, Jie Tian*, Multi-focus Network to Decode Imaging Phenotype for Overall Survival Prediction of Gastric Cancer Patients, IEEE Journal of Biomedical and Health Informatics, 2021, 25(10): 3933-3942. Date of Publication: 08 June 2021. DOI: 10.1109/JBHI.2021.3087634.

38.  Siwen Wang#, Di Dong#, Liang Li#, Hailin Li, Yan Bai, Yahua Hu, Yuanyi Huang, Xiangrong Yu, Sibin Liu, Xiaoming Qiu, Ligong Lu, Meiyun Wang, Yunfei Zha*, Jie Tian*, A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients with Underlying Health Conditions: A Multicenter Study, IEEE Journal of Biomedical and Health Informatics, 2021, 25(7): 2353-2362. Date of Publication: 27 April 2021. DOI: 10.1109/JBHI.2021.3076086.

39.  Cong Li#, Di Dong#, Liang Li#, Wei Gong, Xiaohu Li, Yan Bai, Meiyun Wang, Zhenhua Hu*, Yunfei Zha*, Jie Tian*, Classification of Severe and Critical COVID-19 Using Deep Learning and Radiomics, IEEE Journal of Biomedical and Health Informatics, 2020, 24(12): 3585-3594. Published: 09 November 2020. DOI: 10.1109/jbhi.2020.3036722.

40.  Lingwei Meng#, Di Dong#, Liang Li#, Meng Niu, Yan Bai, Meiyun Wang, Xiaoming Qiu, Yunfei Zha*, Jie Tian*, A Deep Learning Prognosis Model Help Alert for COVID-19 Patients at High-Risk of Death: A Multi-center Study, IEEE Journal of Biomedical and Health Informatics, 2020, 24(12): 3576-3584. Published: 27 October 2020. DOI: 10.1109/JBHI.2020.3034296.