Mengjie Fang

According to our database, Mengjie Fang authored at least 14 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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, Di Dong, Yinghua Zou

Vis. Comput. Ind. Biomed. Art, December, 2024

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, Feng Chen

Vis. Comput. Ind. Biomed. Art, December, 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

Neural Networks, July, 2023

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

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

2022

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

Comput. Biol. Medicine, 2022

2021

2D and 3D CT Radiomic Features Performance Comparison in Characterization of Gastric Cancer: A Multi-Center Study.

Lingwei Meng, Di Dong, Xin Chen, Mengjie Fang, Rongpin Wang, Jing Li, Zaiyi Liu, Jie Tian

IEEE J. Biomed. Health Informatics, 2021

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, Xiuhong Shan

BMC Medical Imaging, 2021

2020

CT radiomics can help screen the Coronavirus disease 2019 (COVID-19): a preliminary study.

Mengjie Fang, Bingxi He, Li Li, Di Dong, Xin Yang, Cong Li, Lingwei Meng, Lianzhen Zhong, Hailin Li, Hongjun Li, Jie Tian

Sci. China Inf. Sci., 2020

2019

Predicting histopathological findings of gastric cancer via deep generalized multi-instance learning.

Mengjie Fang, Wenjuan Zhang, Di Dong, Junlin Zhou, Jie Tian

Proceedings of the Medical Imaging 2019: Image Processing, 2019

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

Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019

2018

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

Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

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

Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

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, Wenzhao Zhong, Jingyun Shi, Di Dong, Mengjie Fang, Zaiyi Liu, Jie Tian

Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

2016

Learning evaluation of ultrasound image segmentation using combined measures.

Mengjie Fang, Yongkang Luo, Mingyue Ding

Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016