强宁｜陕西师范大学｜学者主页

2027

Edge-attention graph convolutional network for depression grading via EEG cross-network interaction analysis

Zheng-Zheng Ru, Jia-Xin Tai, Meng-Yuan Liu, Xu Zhang, Li-Wei Guo, Ying Cai, Jing Hu, Jin Li, Ning Qiang

Biomedical Signal Processing and Control

DOI

2026

基于U2-Net和CBAM融合注意力的双模态睡眠分期研究

赵倩，李锦，凤飞龙，强宁，胡静

《陕西师范大学学报(自然科学版)》

DOI

2026

FNF: Functional Network Fingerprint for Large Language Models

Yi-Heng Liu, Jun-Hao Ning, Si-Chen Xia, Haiyang Sun, Yang Yang, Hanyang Chi, Xiaohui Gao, Ning Qiang, Bao Ge, Junwei Han, Xintao Hu

arXiv.org

DOI

2026

WaveCrossNet: interpretable cross-modal automatic sleep staging for OSA patients

Ruomeng Quan, Jia-Xin Tai, Meng-Yuan Liu, Xu Zhang, Yan-Yan Xiao, Jing-Jing Yu, Jing Hu, Jin Li, Ning Qiang

Biomedical engineering and physics express

DOI

2025

基于单通道脑电的跨域自动睡眠分期

朱梦圆，全若梦，强宁，胡静，凤飞龙，李锦

《中国生物医学工程学报》

2025

基于深度学习和功能磁共振影像的脑网络检测研究综述

孙晨静，冯茹苹，杨渊元，马思源，常雨昕，高洁，葛宝，赵世杰，李锦，强宁

《陕西师范大学学报(自然科学版)》

DOI

2025

Combining static and dynamic brain network analysis with machine learning for enhanced diagnosis of major depressive disorder.

Chenjing Sun, Ru-Ping Feng, Meng-Yuan Liu, Siyuan Ma, Jia-Xin Tai, Jing Hu, Jin Li, Ning Qiang

Psychiatry research. Neuroimaging

DOI

2025

Exploring the changes in brain network SC-FC coupling patterns of partial sleep deprivation based on DTI-fMRI fusion analysis

Meng-Yuan Liu, Jing Hu, Zheng-Zheng Ru, Ruomeng Quan, Xu Zhang, Ning Qiang, Jin Li

2025

3D masked autoencoder with spatiotemporal transformer for modeling of 4D fMRI data

Jie Gao, Bao Ge, Ning Qiang, Shi-Shun Zhao

Medical Image Anal.

DOI

2025

Pruning Large Language Models by Identifying and Preserving Functional Networks

Yi-Heng Liu, Jun-Hao Ning, Si-Chen Xia, Xiaohui Gao, Ning Qiang, Bao Ge, Junwei Han, Xintao Hu

arXiv.org

DOI

2025

Brain-Inspired Exploration of Functional Networks and Key Neurons in Large Language Models

Yi-Heng Liu, Zheng Liu, Zi-Hao Wu, Jun-Hao Ning, Haiyang Sun, Si-Chen Xia, Yang Yang, Xiaohui Gao, Ning Qiang, Bao Ge, Tianming Liu, Jun-Feng Han, Xintao Hu

arXiv.org

DOI

2024

Spatial-temporal convolutional attention for discovering and characterizing functional brain networks in task fMRI

Yi-Heng Liu, Enjie Ge, Zili Kang, Ning Qiang, Tian-Ming Liu, Bao Ge

NeuroImage

DOI

2024

Mapping dynamic spatial patterns of brain function with spatial-wise attention

Yi-Heng Liu, Enjie Ge, Mengshen He, Zheng Liu, Shi-Jie Zhao, Xin-Tao Hu, Ning Qiang, Da-Jiang Zhu, Tian-Ming Liu, Bao Ge

Journal of Neural Engineering

DOI

2024

Deep Linear Matrix Approximate Reconstruction Reveals Reproducible Large-Scale Functional Connectivity Networks in the Human Brain

Wei Zhang, Xi Jiang, Shijie Zhao, Ning Qiang, Yu Bao, Jing-Lei Lv

MCHM@MM

DOI

2024

A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks

Jiaqi Wang, Han-Qi Jiang, Yi-Heng Liu, Chong Ma, Xu Zhang, Yi Pan, Meng-Yuan Liu, Pei-Ran Gu, Si-Chen Xia, Wen-Jun Li, Yu-Tong Zhang, Zi-Hao Wu, Zheng Liu, Tianyang Zhong, Bao Ge, Tuo Zhang, Ning Qiang, Xin-Tao Hu, Xi Jiang, Xin Zhang, Wei Zhang, Dinggang Shen, Tianming Liu, Shu Zhang

arXiv.org

DOI

2024

Understanding LLMs: A Comprehensive Overview from Training to Inference

Yi-Heng Liu, Haoyang He, Tianle Han, Xu Zhang, Meng-Yuan Liu, Jiaming Tian, Yu-Tong Zhang, Jiaqi Wang, Xiaohui Gao, Tianyang Zhong, Yi Pan, Shao-Chen Xu, Zihao Wu, Zheng Liu, Xin Zhang, Shu Zhang, Xin-Tao Hu, Tuo Zhang, Ning Qiang, Tian-Ming Liu, Bao Ge

Neurocomputing

DOI

2023

A deep learning method for autism spectrum disorder identification based on interactions of hierarchical brain networks

Ning Qiang, Jie Gao, Qinglin Dong, Jin Li, Shu Zhang, Hongtao Liang, Yifei Sun, Bao Ge, Zhengliang Liu, Zihao Wu, Tianming Liu, Huiji Yue, Shijie Zhao

Behavioural Brain Research，Vol. 452

DOI

2023

End-to-End Prediction of EGFR Mutation Status With Denseformer

Shi-Jie Zhao, Wenyuan Li, Zhuoyan Liu, Tianji Pang, Yang Yang, Ning Qiang, Jingyi Zhao, Bangguo Li, Bai-Ying Lei, J. Han

IEEE journal of biomedical and health informatics

DOI

2023

Holistic Evaluation of GPT-4V for Biomedical Imaging

Zheng Liu, Han-Qi Jiang, Tianyang Zhong, Zihao Wu, Chong Ma, Yi-Wei Li, Xiaowei Yu, Yu-Tong Zhang, Yi Pan, Peng Shu, Yanjun Lyu, Lu Zhang, Junjie Yao, Peixin Dong, C. Cao, Zhe Xiao, Jiaqi Wang, Huan Zhao, Shao-Chen Xu, Yao-Nai Wei, Jing-Yuan Chen, Hai-Xing Dai, Pei-Long Wang, Haoyang He, Ze-Wei Wang, Xinyu Wang, Xu Zhang, Lin Zhao, Yi-Heng Liu, Kai Zhang, Liheng Yan, Li-Chao Sun, Jun Liu, Ning Qiang, Bao Ge, Xiaoyan Cai, Shijie Zhao, Xin-Tao Hu, Yi Yuan, Gang Li, Shu Zhang, Xin Zhang, Xi Jiang, Tuo Zhang, Dinggang Shen, Quan-Zheng Li, Wei Liu, Xiang Li, Da-Jiang Zhu, Tian-Ming Liu

arXiv.org

DOI

2023

Accurate corresponding fiber tract segmentation via FiberGeoMap learner with application to autism.

Zhenwei Wang, Mengshen He, Yifan Lv, Enjie Ge, Shu Zhang, Ning Qiang, Tian-Ming Liu, Fan Zhang, Xiang Li, Bao Ge

Cerebral Cortex

DOI

2023

Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models

Yi-Heng Liu, Tianle Han, Si-Yuan Ma, Jia-Yu Zhang, Yuanyu Yang, Jiaming Tian, Haoyang He, Antong Li, Mengshen He, Zheng Liu, Zihao Wu, Lin Zhao, Da-Jiang Zhu, Xiang Li, Ning Qiang, Dinggang Shen, Tianming Liu, Bao Ge

Meta-Radiology

DOI

2023

Multi-head attention-based masked sequence model for mapping functional brain networks

Mengshen He, Xiangyu Hou, Enjie Ge, Zhenwei Wang, Zili Kang, Ning Qiang, Xin Zhang, Bao Ge

Frontiers in Neuroscience

DOI

2023

Functional brain network identification and fMRI augmentation using a VAE-GAN framework

Ning Qiang, Jie Gao, Qinglin Dong, Huiji Yue, Hongtao Liang, Li-Li Liu, Jing-Jing Yu, Jing Hu, Shenmin Zhang, Bao Ge, Yifei Sun, Zheng Liu, Tianming Liu, Jin Li, Hujie Song, Shi-Jie Zhao

Comput. Biol. Medicine

DOI

2022

Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner

Zhenwei Wang, Yifan Lv, Mengshen He, Enjie Ge, Ning Qiang, Bao Ge

International Conference on Medical Image Computing and Computer-Assisted Intervention

DOI

2022

An Explainable and Generalizable Recurrent Neural Network Approach for Differentiating Human Brain States on EEG Dataset

Shenmin Zhang, Lin Wu, Sigang Yu, En-Ze Shi, Ning Qiang, Huan Gao, Jingyi Zhao, Shi-Jie Zhao

IEEE Transactions on Neural Networks and Learning Systems

DOI

2022

A novel ADHD classification method based on resting state temporal templates (RSTT) using spatiotemporal attention auto-encoder

Ning Qiang, Qinglin Dong, Hongtao Liang, Bao Ge, Shenmin Zhang, Cheng Zhang, Jie Gao, Yifei Sun

Neural computing & applications (Print)

DOI

2022

Multi-head Attention-Based Masked Sequence Model for Mapping Functional Brain Networks

Mengshen He, Xiangyu Hou, Zhenwei Wang, Zili Kang, Xin Zhang, Ning Qiang, Bao Ge

International Conference on Medical Image Computing and Computer-Assisted Intervention

DOI

2022

Spatial-Temporal Convolutional Attention for Mapping Functional Brain Networks

Yi-Heng Liu, Enjie Ge, Ning Qiang, Tianming Liu, Bao Ge

IEEE International Symposium on Biomedical Imaging

DOI

2022

Learning brain representation using recurrent Wasserstein generative adversarial net

Ning Qiang, Qinglin Dong, Hongtao Liang, Jin Li, Shenmin Zhang, Cheng Zhang, Bao Ge, Yifei Sun, Jie Gao, Tianming Liu, Huiji Yue, Shi-Jie Zhao

Comput. Methods Programs Biomed.

DOI

2021

Modeling and augmenting of fMRI data using deep recurrent variational auto-encoder

Ning Qiang, Qinglin Dong, Hongtao Liang, Bao Ge, Shu Zhang, Yifei Sun, Cheng Zhang, Wei Zhang, Jie Gao, Tianming Liu

Journal of Neural Engineering

DOI

2021

Simultaneous spatial-temporal decomposition for connectome-scale brain networks by deep sparse recurrent auto-encoder

Qing Li, Qinglin Dong, Fangfei Ge, Ning Qiang, Xia Wu, Tianming Liu

Brain Imaging and Behavior

DOI

2020

Task fMRI Guided Fiber Clustering via a Deep Clustering Method

Huan Wang, Qinglin Dong, Ning Qiang, Xin Zhang, Tianming Liu, Bao Ge

IEEE International Symposium on Biomedical Imaging

DOI

2020

Deep Variational Autoencoder for Modeling Functional Brain Networks and ADHD Identification

Ning Qiang, Qinglin Dong, Yifei Sun, Bao Ge, Tianming Liu

IEEE International Symposium on Biomedical Imaging

DOI

2020

Modeling Task-based fMRI Data via Deep Belief Network with Neural Architecture Search

Ning Qiang, Qinglin Dong, Wei Zhang, Bao Ge, Fangfei Ge, Hongtao Liang, Yifei Sun, Jie Gao, Tianming Liu

Comput. Medical Imaging Graph.

DOI

2020

Spatiotemporal Attention Autoencoder (STAAE) for ADHD Classification

Qinglin Dong, Ning Qiang, Jing-Lei Lv, Xiang Li, Tianming Liu, Quan-Zheng Li

International Conference on Medical Image Computing and Computer-Assisted Intervention

DOI

2020

A Novel fMRI Representation Learning Framework with GAN

Qinglin Dong, Ning Qiang, Jing-Lei Lv, Xiang Li, Liang Dong, Tianming Liu, Quan-Zheng Li

MLMI@MICCAI

DOI

2020

Discovering Functional Brain Networks with 3D Residual Autoencoder (ResAE)

Qinglin Dong, Ning Qiang, Jing-Lei Lv, Xiang Li, Tianming Liu, Quan-Zheng Li

International Conference on Medical Image Computing and Computer-Assisted Intervention

DOI

2020

Deep Variational Autoencoder for Mapping Functional Brain Networks

Ning Qiang, Qinglin Dong, Fangfei Ge, Hongtao Liang, Bao Ge, Shu Zhang, Yifei Sun, Jie Gao, Tianming Liu

IEEE Transactions on Cognitive and Developmental Systems

DOI

2019

Simultaneous Spatial-Temporal Decomposition of Connectome-Scale Brain Networks by Deep Sparse Recurrent Auto-Encoders

Qing Li, Qinglin Dong, Fangfei Ge, Ning Qiang, Yu Zhao, Han Wang, Heng Huang, Xia Wu, Tian-Ming Liu

Information Processing in Medical Imaging

DOI

2019

Neural Architecture Search for Optimizing Deep Belief Network Models of fMRI Data

Ning Qiang, Bao Ge, Qinglin Dong, Fangfei Ge, Tianming Liu

MMMI@MICCAI

DOI

2019

Modeling Hierarchical Brain Networks via Volumetric Sparse Deep Belief Network

Qinglin Dong, Fangfei Ge, Ning Qiang, Yu Zhao, Jinglei Lv, Heng Huang, Jing Yuan, Xi Jiang, Dinggang G. Shen, Tianming Liu

IEEE Transactions on Biomedical Engineering

DOI

2017

空間スペクトル制約のある高分解能MR分光イメージングのためのスペクトル定量化【Powered by NICT】

Ning Qiang, Chao Ma, L. Fan, Zhi-Pei Liang

精选作品

期刊论文

Edge-attention graph convolutional network for depression grading via EEG cross-network interaction analysis

基于U2-Net和CBAM融合注意力的双模态睡眠分期研究

FNF: Functional Network Fingerprint for Large Language Models

WaveCrossNet: interpretable cross-modal automatic sleep staging for OSA patients

基于单通道脑电的跨域自动睡眠分期

基于深度学习和功能磁共振影像的脑网络检测研究综述

Combining static and dynamic brain network analysis with machine learning for enhanced diagnosis of major depressive disorder.

Exploring the changes in brain network SC-FC coupling patterns of partial sleep deprivation based on DTI-fMRI fusion analysis

3D masked autoencoder with spatiotemporal transformer for modeling of 4D fMRI data

Pruning Large Language Models by Identifying and Preserving Functional Networks

Brain-Inspired Exploration of Functional Networks and Key Neurons in Large Language Models

Spatial-temporal convolutional attention for discovering and characterizing functional brain networks in task fMRI

Mapping dynamic spatial patterns of brain function with spatial-wise attention

Deep Linear Matrix Approximate Reconstruction Reveals Reproducible Large-Scale Functional Connectivity Networks in the Human Brain

A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks

Understanding LLMs: A Comprehensive Overview from Training to Inference

A deep learning method for autism spectrum disorder identification based on interactions of hierarchical brain networks

End-to-End Prediction of EGFR Mutation Status With Denseformer

Holistic Evaluation of GPT-4V for Biomedical Imaging

Accurate corresponding fiber tract segmentation via FiberGeoMap learner with application to autism.

Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models

Multi-head attention-based masked sequence model for mapping functional brain networks

Functional brain network identification and fMRI augmentation using a VAE-GAN framework

Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner

An Explainable and Generalizable Recurrent Neural Network Approach for Differentiating Human Brain States on EEG Dataset

A novel ADHD classification method based on resting state temporal templates (RSTT) using spatiotemporal attention auto-encoder

Multi-head Attention-Based Masked Sequence Model for Mapping Functional Brain Networks

Spatial-Temporal Convolutional Attention for Mapping Functional Brain Networks

Learning brain representation using recurrent Wasserstein generative adversarial net

Modeling and augmenting of fMRI data using deep recurrent variational auto-encoder

Simultaneous spatial-temporal decomposition for connectome-scale brain networks by deep sparse recurrent auto-encoder

Task fMRI Guided Fiber Clustering via a Deep Clustering Method

Deep Variational Autoencoder for Modeling Functional Brain Networks and ADHD Identification

Modeling Task-based fMRI Data via Deep Belief Network with Neural Architecture Search

Spatiotemporal Attention Autoencoder (STAAE) for ADHD Classification

A Novel fMRI Representation Learning Framework with GAN

Discovering Functional Brain Networks with 3D Residual Autoencoder (ResAE)

Deep Variational Autoencoder for Mapping Functional Brain Networks

Simultaneous Spatial-Temporal Decomposition of Connectome-Scale Brain Networks by Deep Sparse Recurrent Auto-Encoders

Neural Architecture Search for Optimizing Deep Belief Network Models of fMRI Data

Modeling Hierarchical Brain Networks via Volumetric Sparse Deep Belief Network

空間スペクトル制約のある高分解能MR分光イメージングのためのスペクトル定量化【Powered by NICT】

预印本

Dynamic State-Driven Spatiotemporal Framework for Interpretable Modeling of EEG Data in ADHD Classification

书籍章节

Deep learning in functional brain mapping and associated applications

研究方向