World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
66
Citations
20893
World Ranking
2290
National Ranking
314

Research.com Recognitions

  • 2020 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to fuzzy clustering, dimensionality reduction, and medical image analysis

Overview

Daoqiang Zhang is affiliated with Nanjing University of Aeronautics and Astronautics in China. Their research spans several interdisciplinary fields, primarily focused on the intersection of computer science, medicine, and neuroscience.

The scientist has contributed extensively to topics such as functional brain connectivity studies, EEG and brain-computer interfaces, AI in cancer detection, brain tumor detection and classification, medical image segmentation techniques, radiomics and machine learning in medical imaging, and advanced neuroimaging techniques and applications.

Recent notable publications by Daoqiang Zhang include:

  • "Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT" (2020, IEEE Journal of Biomedical and Health Informatics)
  • "Dual Attention Multi-Instance Deep Learning for Alzheimer's Disease Diagnosis With Structural MRI" (2021, IEEE Transactions on Medical Imaging)
  • "A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis" (2020, Frontiers in Neuroscience)
  • "An Explainable 3D Residual Self-Attention Deep Neural Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI" (2021, IEEE Journal of Biomedical and Health Informatics)
  • "Cognitive Workload Recognition Using EEG Signals and Machine Learning: A Review" (2021, IEEE Transactions on Cognitive and Developmental Systems)

Frequent co-authors collaborating with Daoqiang Zhang include:

  • Wei Shao (45 collaborations)
  • Qi Zhu (41 collaborations)
  • Dinggang Shen (31 collaborations)
  • Fang Chen (30 collaborations)
  • Liang Sun (28 collaborations)

The scientist has published in various venues, demonstrating a breadth of dissemination channels predominantly oriented toward medical imaging and computational neuroscience. Key publication venues include:

  • UNC Libraries (30 publications)
  • arXiv (Cornell University) (30 publications)
  • IEEE Transactions on Medical Imaging (26 publications)
  • IEEE Transactions on Neural Systems and Rehabilitation Engineering (10 publications)
  • Medical Image Analysis (9 publications)

Daoqiang Zhang's primary fields of study are computer science, medicine, and neuroscience, with significant work also situated in specialized subfields including cognitive neuroscience, radiology, nuclear medicine and imaging, artificial intelligence, computer vision and pattern recognition, and biomedical engineering.

In recognition of contributions to the domains of fuzzy clustering, dimensionality reduction, and medical image analysis, Daoqiang Zhang was named a Fellow of the International Association for Pattern Recognition (IAPR) in 2020.

Best Publications

  • Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure

    Songcan Chen;Daoqiang Zhang

  • Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

    Daoqiang Zhang;Yaping Wang;Luping Zhou;Hong Yuan

  • Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation

    Weiling Cai;Songcan Chen;Daoqiang Zhang

  • Multi-modal multi-task learning for joint prediction of multiple regression and classification variables in Alzheimer's disease

    Daoqiang Zhang;Daoqiang Zhang;Dinggang Shen

  • Letters: (2D)2PCA: Two-directional two-dimensional PCA for efficient face representation and recognition

    Daoqiang Zhang;Zhi-Hua Zhou

  • A novel kernelized fuzzy C-means algorithm with application in medical image segmentation

    Dao-Qiang Zhang;Song-Can Chen

  • Identification of MCI individuals using structural and functional connectivity networks

    Chong Yaw Wee;Pew Thian Yap;Daoqiang Zhang;Kevin Denny

  • Semi-Supervised Dimensionality Reduction.

    Daoqiang Zhang;Zhi-Hua Zhou;Songcan Chen

  • Clustering Incomplete Data Using Kernel-Based Fuzzy C-means Algorithm

    Dao-Qiang Zhang;Song-Can Chen

  • Ensemble Sparse Classification of Alzheimer’s Disease

    Manhua Liu;Daoqiang Zhang;Daoqiang Zhang;Dinggang Shen

  • Predicting Future Clinical Changes of MCI Patients Using Longitudinal and Multimodal Biomarkers

    Daoqiang Zhang;Daoqiang Zhang;Dinggang Shen;Alzheimer's Disease Neuroimaging Initiative

  • Constraint Score: A new filter method for feature selection with pairwise constraints

    Daoqiang Zhang;Songcan Chen;Zhi-Hua Zhou

  • A new face recognition method based on SVD perturbation for single example image per person

    Daoqiang Zhang;Songcan Chen;Zhi-Hua Zhou

  • Dual Attention Multi-Instance Deep Learning for Alzheimer’s Disease Diagnosis With Structural MRI

    Wenyong Zhu;Liang Sun;Jiashuang Huang;Liangxiu Han

  • Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT

    Liang Sun;Zhanhao Mo;Fuhua Yan;Liming Xia

  • A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis.

    Li Zhang;Li Zhang;Mingliang Wang;Mingxia Liu;Daoqiang Zhang

  • Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment

    Mingxia Liu;Daoqiang Zhang;Dinggang Shen

  • Domain Transfer Learning for MCI Conversion Prediction

    Bo Cheng;Mingxia Liu;Daoqiang Zhang;Brent C. Munsell

  • Multi-modal Neuroimaging Feature Selection with Consistent Metric Constraint for Diagnosis of Alzheimer’s Disease

    Xiaoke Hao;Yongjin Bao;Yingchun Guo;Ming Yu

  • Group-constrained sparse fMRI connectivity modeling for mild cognitive impairment identification

    Chong Yaw Wee;Pew Thian Yap;Daoqiang Zhang;Daoqiang Zhang;Lihong Wang

  • Enhanced (PC) 2 A for face recognition with one training image per person

    Songcan Chen;Daoqiang Zhang;Zhi-Hua Zhou

  • Rapid and brief communication: Diagonal principal component analysis for face recognition

    Daoqiang Zhang;Zhi-Hua Zhou;Songcan Chen

  • Integration of Network Topological and Connectivity Properties for Neuroimaging Classification

    Biao Jie;Daoqiang Zhang;Wei Gao;Qian Wang

Frequent Co-Authors

Dinggang Shen
Dinggang Shen ShanghaiTech University
Mingxia Liu
Mingxia Liu University of North Carolina at Chapel Hill
Songcan Chen
Songcan Chen Nanjing University of Aeronautics and Astronautics
Zhi-Hua Zhou
Zhi-Hua Zhou Nanjing University
Li Shen
Li Shen University of Pennsylvania
Chong Yaw Wee
Chong Yaw Wee University of North Carolina at Chapel Hill
Guorong Wu
Guorong Wu University of North Carolina at Chapel Hill
Pew Thian Yap
Pew Thian Yap University of North Carolina at Chapel Hill
Jun Liu
Jun Liu Infinia ML (United States)
Teng Jiang
Teng Jiang Nanjing Medical University

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