Learning evaluation of ultrasound image segmentation using combined measures. - Mengjie Fang; Yongkang Luo 002; Mingyue Ding (Computer-Aided Diagnosis, 2016)

Development and validation of a radiomics nomogram for progression-free survival prediction in stage IV EGFR-mutant non-small cell lung cancer. - Jiangdian Song; Yali Zang; Weimin Li 003; Wenzhao Zhong; Jingyun Shi; Di Dong; Mengjie Fang; Zaiyi Liu; Jie Tian 001 (Computer-Aided Diagnosis, 2017)

Developing a radiomics framework for classifying non-small cell lung carcinoma subtypes. - Dongdong Yu; Yali Zang; Di Dong; Mu Zhou; Olivier Gevaert; Mengjie Fang; Jingyun Shi; Jie Tian 001 (Computer-Aided Diagnosis, 2017)

Radiomics analysis of DWI data to identify the rectal cancer patients qualified for local excision after neoadjuvant chemoradiotherapy. - Zhenchao Tang; Zhenyu Liu; Xiaoyan Zhang; Yanjie Shi; Shou Wang; Mengjie Fang; Yingshi Sun; Enqing Dong; Jie Tian 001 (Computer-Aided Diagnosis, 2018)

Using multi-task learning to improve diagnostic performance of convolutional neural networks. - Mengjie Fang; Di Dong; Ruijia Sun; Li Fan; Yingshi Sun; Shiyuan Liu; Jie Tian 001 (Computer-Aided Diagnosis, 2019)

Predicting histopathological findings of gastric cancer via deep generalized multi-instance learning. - Mengjie Fang; Wenjuan Zhang; Di Dong; Junlin Zhou; Jie Tian 001 (Image Processing, 2019)

CT radiomics can help screen the Coronavirus disease 2019 (COVID-19): a preliminary study. - Mengjie Fang; Bingxi He; Li Li; Di Dong; Xin Yang 001; Cong Li; Lingwei Meng; Lianzhen Zhong; Hailin Li; Hongjun Li; Jie Tian 001 (Sci. China Inf. Sci., 2020)

Integrating No.3 lymph nodes and primary tumor radiomics to predict lymph node metastasis in T1-2 gastric cancer. - Xiaoxiao Wang; Cong Li; Mengjie Fang; Liwen Zhang; Lianzhen Zhong; Di Dong; Jie Tian 001; Xiuhong Shan (BMC Medical Imaging, 2021)

2D and 3D CT Radiomic Features Performance Comparison in Characterization of Gastric Cancer: A Multi-Center Study. - Lingwei Meng; Di Dong; Xin Chen 058; Mengjie Fang; Rongpin Wang; Jing Li; Zaiyi Liu; Jie Tian 001 (IEEE J. Biomed. Health Informatics, 2021)

The potential of prostate gland radiomic features in identifying the Gleason score. - Lixin Gong; Min Xu; Mengjie Fang; Bingxi He; Hailin Li; Xiangming Fang; Di Dong; Jie Tian 001 (Comput. Biol. Medicine, 2022)

Multi-task Residual Cross-attention Network for Tumor Segmentation and Lymph Node Metastasis Prediction in Cervical Cancer. - Shengyuan Liu; Mengjie Fang; Di Dong; Wenting Shang; Jie Tian 001 (ISBI, 2023)

A multi-view co-training network for semi-supervised medical image-based prognostic prediction. - Hailin Li; Siwen Wang; Bo Liu; Mengjie Fang; Runnan Cao; Bingxi He; Shengyuan Liu; Chaoen Hu; Di Dong; Ximing Wang; Hexiang Wang; Jie Tian 001 (Neural Networks, 2023)

Comprehensive integrated analysis of MR and DCE-MR radiomics models for prognostic prediction in nasopharyngeal carcinoma. - Hailin Li; Weiyuan Huang; Siwen Wang; Priya S. Balasubramanian; Gang Wu; Mengjie Fang; Xuebin Xie; Jie Zhang; Di Dong; Jie Tian 001; Feng Chen (Vis. Comput. Ind. Biomed. Art, 2023)

Enhancing Prognostic Prediction of Gastrointestinal Stromal Tumors Using Semi-Supervised Regression Based on CT Imaging Data. - Hailin Li; Mengjie Fang; Bingxi He; Di Dong; Jie Tian 001 (EMBC, 2024)

CT-based radiomics: predicting early outcomes after percutaneous transluminal renal angioplasty in patients with severe atherosclerotic renal artery stenosis. - Jia Fu; Mengjie Fang; Zhiyong Lin; Jianxing Qiu; Min Yang; Jie Tian 001; Di Dong; Yinghua Zou (Vis. Comput. Ind. Biomed. Art, 2024)

ContraSurv: Enhancing Prognostic Assessment of Medical Images via Data-Efficient Weakly Supervised Contrastive Learning. - Hailin Li; Di Dong; Mengjie Fang; Bingxi He; Shengyuan Liu; Chaoen Hu; Zaiyi Liu; Hexiang Wang; Linglong Tang; Jie Tian 001 (IEEE J. Biomed. Health Informatics, 2025)