Shu Zhang
Orcid: 0000-0002-3431-744XAffiliations:
- Northwestern Polytechnical University, School of Computer Science, Xi'an, China
- Stony Brook University, Department of Radiology, NY, USA (former)
According to our database1,
Shu Zhang
authored at least 24 papers
between 2019 and 2024.
Collaborative distances:
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Bibliography
2024
IEEE Trans. Artif. Intell., August, 2024
An Explainable and Generalizable Recurrent Neural Network Approach for Differentiating Human Brain States on EEG Dataset.
IEEE Trans. Neural Networks Learn. Syst., June, 2024
IEEE Trans. Biomed. Eng., May, 2024
IEEE ACM Trans. Comput. Biol. Bioinform., 2024
CoRR, 2024
HARP: Human-Assisted Regrouping with Permutation Invariant Critic for Multi-Agent Reinforcement Learning.
CoRR, 2024
DTCA: Dual-Branch Transformer with Cross-Attention for EEG and Eye Movement Data Fusion.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
2023
Comput. Medical Imaging Graph., September, 2023
An explainable deep learning framework for characterizing and interpreting human brain states.
Medical Image Anal., 2023
Exploring Brain Function-Structure Connectome Skeleton via Self-supervised Graph-Transformer Approach.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
A Novel Multi-Modality Framework for Exploring Brain Connectivity Hubs Via Reinforcement Learning Approach.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
A Diffusion-Based Multi-Objective Ant Colony Algorithm for Optimizing Network Topology Design.
Proceedings of the 9th International Conference on Communication and Information Processing, 2023
2022
An Adaptive Learning Model for Multiscale Texture Features in Polyp Classification via Computed Tomographic Colonography.
Sensors, 2022
A Bagging Strategy-Based Multi-scale Texture GLCM-CNN Model for Differentiating Malignant from Benign Lesions Using Small Pathologically Proven Dataset.
Proceedings of the Multiscale Multimodal Medical Imaging - Third International Workshop, 2022
A Novel Two-Stage Multi-view Low-Rank Sparse Subspace Clustering Approach to Explore the Relationship Between Brain Function and Structure.
Proceedings of the Machine Learning in Medical Imaging - 13th International Workshop, 2022
2020
Predicting Unnecessary Nodule Biopsies from a Small, Unbalanced, and Pathologically Proven Dataset by Transfer Learning.
J. Digit. Imaging, 2020
A multi-stage fusion strategy for multi-scale GLCM-CNN model in differentiating malignant from benign polyps.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Performance investigation of deep learning vs. classifier for polyp differentiation via texture features.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
A deep learning based integration of multiple texture patterns from intensity, gradient and curvature GLCMs in differentiating the malignant from benign polyps.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2019
Energy enhanced tissue texture in spectral computed tomography for lesion classification.
Vis. Comput. Ind. Biomed. Art, 2019
An investigation of CNN models for differentiating malignant from benign lesions using small pathologically proven datasets.
Comput. Medical Imaging Graph., 2019
Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019