Cui-Na Jiao

Orcid: 0000-0001-7479-8105

According to our database1, Cui-Na Jiao authored at least 26 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2026
Deep association analysis framework with multi-modal attention fusion for brain imaging genetics.
Medical Image Anal., 2026

2025
TEMCL: Prediction of Drug-Disease Associations Based on Transformer and Enhanced Multi-View Contrastive Learning.
IEEE J. Biomed. Health Informatics, October, 2025

SpaMGAN: Multi-view graph augmentation network for spatial domain identification in spatial transcriptomics.
Knowl. Based Syst., 2025

SAMGCN: A spatially-augmented multi-view graph convolutional network for identifying spatial domains.
Eng. Appl. Artif. Intell., 2025

STDDAE: Identifying spatial domains in spatial transcriptomics by dual denoising autoencoder with attention mechanism.
Eng. Appl. Artif. Intell., 2025

Multimodal adaptive fusion deep analysis model for Alzheimer's disease exploration and diagnosis.
Comput. Biol. Medicine, 2025

2024
FSCME: A Feature Selection Method Combining Copula Correlation and Maximal Information Coefficient by Entropy Weights.
IEEE J. Biomed. Health Informatics, September, 2024

Deep Self-Reconstruction Fusion Similarity Hashing for the Diagnosis of Alzheimer's Disease on Multi-Modal Data.
IEEE J. Biomed. Health Informatics, June, 2024

Diagnosis-Guided Deep Subspace Clustering Association Study for Pathogenetic Markers Identification of Alzheimer's Disease Based on Comparative Atlases.
IEEE J. Biomed. Health Informatics, May, 2024

Multi-Kernel Graph Attention Deep Autoencoder for MiRNA-Disease Association Prediction.
IEEE J. Biomed. Health Informatics, February, 2024

Multi-modal imaging genetics data fusion by deep auto-encoder and self-representation network for Alzheimer's disease diagnosis and biomarkers extraction.
Eng. Appl. Artif. Intell., 2024

Deep Hyper-Laplacian Regularized Self-representation Learning Based Structured Association Analysis for Brain Imaging Genetics.
Proceedings of the Bioinformatics Research and Applications - 20th International Symposium, 2024

2023
Predicting miRNA-Disease Associations Through Deep Autoencoder With Multiple Kernel Learning.
IEEE Trans. Neural Networks Learn. Syst., September, 2023

Spatial Domain Identification Based on Graph Attention Denoising Auto-encoder.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023

LANCMDA: Predicting MiRNA-Disease Associations via LightGBM with Attributed Network Construction.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023

2022
Visualization and Analysis of Single Cell RNA-Seq Data by Maximizing Correntropy Based Non-Negative Low Rank Representation.
IEEE J. Biomed. Health Informatics, 2022

Kernel risk-sensitive mean p-power loss based hyper-graph regularized robust extreme learning machine and its semi-supervised extension for sample classification.
Appl. Intell., 2022

THSLRR: A Low-Rank Subspace Clustering Method Based on Tired Random Walk Similarity and Hypergraph Regularization Constraints.
Proceedings of the Recent Advances in Transdisciplinary Data Science, 2022

Diagnosing Alzheimer's Disease with Bi-multitask Regularized Sparse Canonical Correlation Analysis and Logistic Regression.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Probability Connectivity-Based Multimodality Regression Analysis for Associating Disease-Specific Multimodal Brain Imaging Phenotypes with Genetic Risk Factors.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021
Bipartite graph-based collaborative matrix factorization method for predicting miRNA-disease associations.
BMC Bioinform., 2021

Sparse Hyper-graph Non-negative Matrix Factorization by Maximizing Correntropy.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020
Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification.
IEEE J. Biomed. Health Informatics, 2020

MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations.
BMC Bioinform., 2020

Locally Manifold Non-negative Matrix Factorization Based on Centroid for scRNA-seq Data Analysis.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019
Hyper-graph Robust Non-negative Matrix Factorization Method for Cancer Sample Clustering and Feature Selection.
Proceedings of the Recent Advances in Data Science, 2019


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