Qianqian Wang
Orcid: 0000-0002-0221-3320Affiliations:
- University of North Carolina at Chapel Hill, Department of Radiology and BRIC, Chapel Hill, NC, USA
- Liaocheng University, School of Mathematics Science, Liaocheng, China
According to our database1,
Qianqian Wang
authored at least 13 papers
between 2022 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
Source-free collaborative domain adaptation via multi-perspective feature enrichment for functional MRI analysis.
Pattern Recognit., 2025
2024
IEEE Trans. Biomed. Eng., August, 2024
Preserving specificity in federated graph learning for fMRI-based neurological disorder identification.
Neural Networks, January, 2024
Triplet-constrained deep hashing for chest X-ray image retrieval in COVID-19 assessment.
Neural Networks, 2024
Augmentation-based Unsupervised Cross-Domain Functional MRI Adaptation for Major Depressive Disorder Identification.
CoRR, 2024
ACTION: Augmentation and Computation Toolbox for Brain Network Analysis with Functional MRI.
CoRR, 2024
Attention-Enhanced Fusion of Structural and Functional MRI for Analyzing HIV-Associated Asymptomatic Neurocognitive Impairment.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
2023
Source-Free Collaborative Domain Adaptation via Multi-Perspective Feature Enrichment for Functional MRI Analysis.
CoRR, 2023
Specificity-Aware Federated Graph Learning for Brain Disorder Analysis with Functional MRI.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
Modularity-Constrained Dynamic Representation Learning for Interpretable Brain Disorder Analysis with Functional MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
2022
Frontiers Neuroinformatics, 2022
Function MRI Representation Learning via Self-supervised Transformer for Automated Brain Disorder Analysis.
Proceedings of the Machine Learning in Medical Imaging - 13th International Workshop, 2022