Yuechen Liu, Zishun Wang, Chen Qiao* and Zongben Xu. GATE: Adaptive learning with working memory by information gating in multi-lamellar hippocampal formation. PLOS Computational Biology, 2026 (Online) https://doi.org/10.1371/journal.pcbi.1014438

Yingying Wang, Kai Ren, Shuo Guo, Jian Yang and Chen Qiao*. Dynamic higher-order causality discovery via reinforcement learning for mild cognitive impairment analysis, Pattern Recognition， 2026, 180， 114150  https://doi.org/10.1016/j.patcog.2026.114150

Yang Lan, Li Yao and Chen Qiao*. Constructing Effective Hyper-Connectivity Networks through Adaptive Directed Hypergraph Embedded Dictionary Learning: Application to Early Mild Cognitive Impairment Detection, IEEE Trans. Medical Imaging, 2026, 45(5), 1918-1932  https://doi.org/10.1109/TMI.2025.3642294

Yiding Wang, Chao Jin, Jian Yang and Chen Qiao*. Time-Reversal Enhanced Dynamic Causality Distribution Learning and Its Application in Identifying Dynamic ECNs in MCI Patients, IEEE Trans. Biomedical Engineering, 2026, 73(1), 180-190  https://doi.org/10.1109/TBME.2025.3579378

Xing Li, Jiawei Chen, Yiming Shi, Miao Li, Jiaqi Liu, Bo Zhang, Yan Yang, Chen Qiao*, Ji Wu and Jianhua Ma, SegReg-Rep: Region-Aware Vision-Language Alignment for Fine-Grained Radiology Report Generation from 3D Medical Images,  IEEE Trans. Radiation and Plasma Medical Sciences, DOI: 10.1109/TRPMS.2026.3693637

Bin Gao, Aiju Yu, Chen Qiao*, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson and Yuping Wang. An Explainable Unified Framework of Spatio-Temporal Coupling Learning with Application to Dynamic Brain Functional Connectivity Analysis, IEEE Trans. Medical Imaging, 2025, 44(2), 941-951 

Faming Xu, Yiding Wang, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang, Chen Qiao*. A Deep Spatio-Temporal Architecture for Dynamic ECN Analysis with Granger Causality based Causal Discovery, Pattern Recognition, 2025, 172, 112346. DOI:10.1016/j.patcog.2025.112346

Lan Yang, Chen Qiao*, Takafumi Kanamori, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson and Yuping Wang. Tensor Dictionary-Based Heterogeneous Transfer Learning to Study Emotion-Related Gender Differences in Brain, Neural Networks, 2025, 183:106974 

Han Yang, Jiao Zhang, Lijiang Shao, Chao Jin, Jian Yang and Chen Qiao*. T-CADiff: Conditional guidance based diffusion model for medical image segmentation,Biomedical Signal Processing and Control, 2025, 110, 108139

Longyun Chen, Yuhui Yang, Aiju Yu, Shuo Guo, Kai Ren, Qinfang Liu, Chen Qiao∗, An explainable spatio-temporal graph convolutional network for the biomarkers identification of ADHD, Biomedical Signal Processing and Control, 2025, 99, 106913

Jiao Zhang, Zhang Qiming, Chen Qiao*, Zhandong Mei, Kai Ren, Jian Chen. YOLOv5-CE-DAFF: A polyp detection model based on CBAM-ECA attention mechanism and dropout-based adaptive feature fusion. Soft Computing, 2025. DOI:10.1007/s00500-025-10895-3

Qiang Li, Wei Huang, Chen Qiao, Huafu Chen. Unraveling Integration-Segregation Imbalances in Schizophrenia Through Topological High-Order Functional Connectivity, Neuroinformatics, 2025, 23:21. DOI:10.1007/s12021-025-09718-5

Yingying Wang, Chen Qiao∗, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson and Yu-Ping Wang, A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity during Brain Development, IEEE Trans. Biomedical Engineering, 2024, 71(12), 3390-3401

Longyun Chen, Chen Qiao∗, Kai Ren, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang, Explainable spatio-temporal graph evolution learning with applications to dynamic brain network analysis during development, NeuroImage, 2024, 298, 120771

Chen Qiao, Bin Gao, Yuechen Liu, Xinyu Hu, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang, Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity, Medical Image Analysis, 2023, 90, 102941

Lan Yang, Chen Qiao∗, Huiyu Zhou, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yuping Wang. Explainable Multimodal Deep Dictionary Learning to Capture Developmental Differences from Three fMRI Paradigms, IEEE Transactions on Biomedical Engineering, 2023, 70(8), 2404-2415

Faming Xu, Chen Qiao∗, Huiyu Zhou, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yuping Wang. An explainable autoencoder with multi-paradigm fMRI fusion for identifying differences in dynamic functional connectivity during brain development, Neural Networks, 2023, 159, 185-197

Ruolin Gong, SiJie He, Tiantian Tian, Jian Chen, Yuewen Hao, Chen Qiao∗. FRCNN-AA-CIF: An automatic detection model of colon polyps based on attention awareness and context information fusion, Computers in Biology and Medicine, 2023, 158, 106787

Jiajia Li, Faming Xu, Na Gao, Yuanqiang Zhu, Yuewen Hao, Chen Qiao∗. Sparse non-convex regularization based explainable DBN in the analysis of brain abnormalities in schizophrenia, Computers in Biology and Medicine,2023, 155, 106664

Chen Qiao, Lan Yang, Yan Shi, Hanfeng Fang and Yanmei Kang. Deep belief networks with self-adaptive sparsity. Applied Intelligence, 2022, 52, 237-253

Weizheng Yan, Gang Qu, Wenxing Hu, Anees Abrol, Biao Cai, Chen Qiao, Sergey M. Plis, Yu-Ping Wang, Jing Sui and Vince D. Calhoun. Deep learning in neuroimaging: promises and challenges. IEEE Signal Processing Magazine, 2022, 39(2): 87-98 

Qi Huang, Chen Qiao*, Kaili Jing, Xu Zhu, Kai Ren. Biomarkers identification for Schizophrenia via VAE and GSDAE-based data augmentation. Computers in Biology and Medicine, 2022, 146, 105603

Aiju Yu, Longyun Chen, Chen Qiao∗. Graph Convolutional Network with Attention Mechanism for Discovering the Brain's Abnormal Activity of Attention Deficit Hyperactivity Disorder, 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2022, 1-5, doi: 10.1109/CISP-BMEI56279.2022.9979902

Chen Qiao, Xin-Yu Hu, Li Xiao, Vince D. Calhoun and Yu-Ping Wang. A deep autoencoder with sparse and graph Laplacian regularization for characterizing dynamic functional connectivity during brain development, Neurocomputing, 2021, 456, 97-108

Chen Qiao, Lan Yang, Vince D. Calhoun, Zong-Ben Xu and Yu-Ping Wang. Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental study, Neural Networks, 2021, 135, 91-104

Xuewu Zhang, Yansheng Gong, Chen Qiao and Wenfeng Jing. Multiview deep learning based on tensor decomposition and its application in fault detection of overhead contact systems. The Visual Computer, 2021, https://doi.org/10.1007/s00371-021-02080-y

Chen Qiao, Yan Shi, Yu-Xian Diao, Vince D. Calhoun and Yu-Ping Wang. Log-sum enhanced sparse deep neural network. Neurocomputing, 2020, 407(24), 206-220 

Chen Qiao, Bin Gao, Yan Shi. SRS-DNN: a deep neural network with strengthening response sparsity. Neural Computing and Applications, 2020, 32(12), 8127-8142

Lan Yang, Shun Qi, Chen Qiao*, Yanmei Kang. Exploring the abnormal brain regions and abnormal functional connections in SZ by multiple hypothesis testing techniques. CMES-Computer Modeling in Engineering & Sciences, 2020, 125(1), 215-237

Na Gao, Chen Qiao*, Shun Qi, Kai Ren, Jian Chen and Han-Feng Fang. Biomarkers selection of abnormal functional connections in Schizophrenia with l2,1-2-norm based sparse regularization feature selection method. In Huang Ds., Jo KH. (eds) Intelligent Computing Theories and Application. ICIC 2020. LNCS 12464, Springer, 145-158, 2020 

Chen Qiao, Jiao Wu and Jian Chen. Application of deep learning in medical image analysis. Shanghai Medical & Pharmaceutical Journal, 2020, 41(23), 14-19. (In Chinese)

Chen Qiao, Bin Gao, Lu-Jia Lu, Vince D. Calhoun and Yu-Ping Wang. Two-Step Feature Selection for Identifying Developmental Differences in Resting fMRI Intrinsic Connectivity Networks. Applied Sciences-Basel, 2019, 9, 4298

Chen Qiao, Lujia Lu, Lan Yang and Paul J. Kennedy. Identifying Brain Abnormalities with Schizophrenia Based on a Hybrid Feature Selection Technology. Applied Sciences-Basel, 2019, 9, 2148

Chen Qiao, Bao Guo. On the Flexible Dynamics Analysis for the Unified Discrete-Time RNNs, Neural Processing Letters, 2019, 50(11): 1755-1771

Chen Qiao, Ke-Feng Sun and Bin Li. A Deep-layer Feature Selection Method Based on Deep Neural Networks, LNCS 10942, Springer, 542-551, 2018

Chen Qiao, Kefeng Sun, Wenfeng Jing and Yan Shi. Critical dynamical analysis for α-UAM RNNs without diagonal nonlinear requirements, Journal of Intelligent & Fuzzy Systems, 2017, 33: 1677-1685

Chen Qiao, Yan Shi, Bin Li and Tai An. A Novel Diagnosis Method for SZ by Deep Neural Networks, Lecture notes in computer science (LNCS 10387), Springer, 433-441, 2017

Chen Qiao, Wenfeng Jing and Yuping Wang. The General Critical Analysis for Continuous-time UPPAM Recurrent Neural Networks. NEUROCOMPUTING, 2016, 175 (Part A): 40-46

Chen Qiao, Dong Liang and Kefeng Sun. Dynamics Analysis for Generic Projection Continuous-time RNNs with Bounded Matrices. JOURNAL OF SYSTEMS SCIENCE AND COMPLEXITY, 2015, 28 (4): 799-812

Chen Qiao, Haibao Chen, Wenfeng Jing and Kefeng Sun. Towards establishing a meaningful and practical dynamics results for the unified RNN model. NEUROCOMPUTING, 2015, 157 (1): 315-322

Dong Liang, Chen Qiao and Zongben Xu. Enhancing Both Efficiency and Representational Capability of Isomap by Extensive Landmark Selection. MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, Article ID 241436

Chen Qiao, Dongdong Lin, Shaolong Cao and Yuping Wang. The Efficient Diagnosis of Schizophrenia by Using Multi-Layer RBMs Deep Networks. 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 603-606, Washington D.C., USA

Li ChunZhong，Zongben Xu, Chen Qiao  and Tao Luo.  Hierarchical clustering driven by cognitive features. SCIENCE CHINA INFORMATION SCIENCES, 2014, 57(1): 1-14

Huizhong Mao,Chen Qiao*, Wenfeng Jing, Xi Chen and Jinqin Mao,  Convergence theory for unified discrete-time RNNs with quasi-symmetric connection, APPLIED MECHANICS AND MATERIALS, 2014, 538: 167-170

Chen Qiao, Wenfeng Jing and Zongben Xu. The UPPAM continuous-time RNN model and its critical dynamics.NEUROCOMPUTING,2013, 106: 158-166

Xi Chen, Huizhong Mao and Chen Qiao*. Without diagonal nonlinear requirements: The more general P-critical dynamical analysis for UPPAM recurrent neural networks.MATHEMATICAL PROBLEMS IN ENGINEERING, 2013, Article ID 760293  http://dx.doi.org/10.1155/2013/760293 

Chen Qiao，Rui Zhang, Jing Yao, Xiangliang Kong, Changsheng Zhou.The research on the GC property for RNNs with limited matrix 2-norm，2013 4th Global Congress on Intelligent Systems (GCIS 2013) Hong Kong, China，82-88

Chen Qiao and Zongben Xu. Critical dynamics study on recurrent neural networks: Globally exponential stability. NEUROCOMPUTING, 2012, 77 (1): 205-211

Chen Qiao. Feasible Convergence analysis for RNNs with linear saturation operator under the negative definition condition. ICEICE 2012, 941-944

Wenfeng Jing, Deyu Meng, Chen Qiao and Zhiming Peng. Eliminating Vertical Stripe Defects on Silicon Steel Surface by L1/2 Regularization. MATHEMATICAL PROBLEMS IN ENGINEERING, 2011, Article ID 854674 

Chen Qiao and Zongben Xu. On the P-critical dynamics analysis of projection recurrent neural networks. NEUROCOMPUTING, 2010, 73 (13-15): 2783-2788 

Chen Qiao and Zongben Xu. A critical global convergence analysis of recurrent neural networks with general projection mappings. NEUROCOMPUTING, 2009, 72 (7-9): 1878-1886

Zongben Xu and Chen Qiao. Towards a unified feedback neural network theory: The uniformly pseudo-projection-anti-monotone net. ACTA MATHEMATICA SINICA-ENGLISH SERIES, 2011, 27 (2): 377-396

Chen Qiao and Zongben Xu. New critical analysis on global convergence of recurrent neural networks with projection mappings. ADVANCES IN NEURAL NETWORKS, 2007: 131-139 

Chen Qiao and Zongben Xu. Global stability analysis of static recurrent neural networks with sigmoidal functions: a unified result. DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS (SERIES A), 2007, 14: 31-35

Chen Qiao and Zongben Xu. The Critically Exponential Stability for Static Continuous Recurrent Neural Networks with Sigmoidal Functions. ACTA MATHEMATICAE APPLICATAE SINICA (In Chinese), 2012，35(6)：961-971

Li ChunZhong，Zongben Xu and Chen Qiao. Hierarchical agglomerative clustering with information feedback. SCIENCE CHINA, F: INFORMATION SCIENCES (In Chinese), 2012，42 (6): 730-742      

Chen Qiao and Zongben Xu. Analysis on Global Convergence for Local Field Recurrent Neural Networks. ACTA MATHEMATICAE APPLICATAE SINICA (In Chinese), 2009, 32 (3): 536-545