2023 - Research.com Computer Science in China Leader Award
2022 - Research.com Computer Science in China Leader Award
2018 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to biomedical applications of pattern recognition and medical image analysis
2017 - Fellow of the Indian National Academy of Engineering (INAE)
His Artificial intelligence study frequently links to other fields, such as Pattern recognition (psychology). His research brings together the fields of Artificial intelligence and Pattern recognition (psychology). He carries out multidisciplinary research, doing studies in Machine learning and Boosting (machine learning). Dinggang Shen integrates many fields in his works, including Boosting (machine learning) and Machine learning. Much of his study explores Classifier (UML) relationship to Domain adaptation. He regularly links together related areas like Classifier (UML) in his Domain adaptation studies. He performs multidisciplinary study in Domain (mathematical analysis) and Mathematical analysis in his work. Dinggang Shen combines Mathematical analysis and Domain (mathematical analysis) in his research. He integrates Statistics and Concordance correlation coefficient in his studies.
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Deep Learning in Medical Image Analysis
Dinggang Shen;Guorong Wu;Heung Il Suk.
Annual Review of Biomedical Engineering (2017)
HAMMER: hierarchical attribute matching mechanism for elastic registration
Dinggang Shen;C. Davatzikos.
IEEE Transactions on Medical Imaging (2002)
Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment
Daoqiang Zhang;Yaping Wang;Luping Zhou;Hong Yuan.
Lane detection and tracking using B-Snake
Yue Wang;Eam Khwang Teoh;Dinggang Shen.
Image and Vision Computing (2004)
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer.
arXiv: Computer Vision and Pattern Recognition (2018)
Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19
Feng Shi;Jun Wang;Jun Shi;Ziyan Wu.
IEEE Reviews in Biomedical Engineering (2021)
Deep convolutional neural networks for multi-modality isointense infant brain image segmentation.
Wenlu Zhang;Rongjian Li;Houtao Deng;Li Wang.
Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis.
Heung-Il Suk;Seong-Whan Lee;Dinggang Shen.
Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans
Jie Zhi Cheng;Dong Ni;Yi Hong Chou;Jing Qin.
Scientific Reports (2016)
Multi-modal multi-task learning for joint prediction of multiple regression and classification variables in Alzheimer's disease
Daoqiang Zhang;Daoqiang Zhang;Dinggang Shen.
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