BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

204 related articles for article (PubMed ID: 35869385)

  • 21. Selecting Multiple Node Statistics Jointly from Functional Connectivity Networks for Brain Disorders Identification.
    Zhang Y; Xue Y; Wu X; Qiao L; Wang Z; Shen D;
    Brain Topogr; 2022 Nov; 35(5-6):559-571. PubMed ID: 36138188
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Remodeling Pearson's Correlation for Functional Brain Network Estimation and Autism Spectrum Disorder Identification.
    Li W; Wang Z; Zhang L; Qiao L; Shen D
    Front Neuroinform; 2017; 11():55. PubMed ID: 28912708
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Low Rank Self-calibrated Brain Network Estimation and Autoweighted Centralized Multi-Task Learning for Early Mild Cognitive Impairment Diagnosis.
    Cheng N; Elazab A; Yang P; Liu D; Yu S; Wang T; Lei B
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():185-188. PubMed ID: 31945874
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Estimating sparse functional brain networks with spatial constraints for MCI identification.
    Xue Y; Zhang L; Qiao L; Shen D
    PLoS One; 2020; 15(7):e0235039. PubMed ID: 32707574
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis.
    Suk HI; Lee SW; Shen D;
    Neuroimage; 2014 Nov; 101():569-82. PubMed ID: 25042445
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment.
    Liu M; Zhang D; Shen D
    IEEE Trans Med Imaging; 2016 Jun; 35(6):1463-74. PubMed ID: 26742127
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Manifold population modeling as a neuro-imaging biomarker: application to ADNI and ADNI-GO.
    Guerrero R; Wolz R; Rao AW; Rueckert D;
    Neuroimage; 2014 Jul; 94():275-286. PubMed ID: 24657351
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Correlation-Weighted Sparse Group Representation for Brain Network Construction in MCI Classification.
    Yu R; Zhang H; An L; Chen X; Wei Z; Shen D
    Med Image Comput Comput Assist Interv; 2016 Oct; 9900():37-45. PubMed ID: 28642938
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Intrinsic functional component analysis via sparse representation on Alzheimer's disease neuroimaging initiative database.
    Jiang X; Zhang X; Zhu D
    Brain Connect; 2014 Oct; 4(8):575-86. PubMed ID: 24846640
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Fusion of ULS Group Constrained High- and Low-Order Sparse Functional Connectivity Networks for MCI Classification.
    Li Y; Liu J; Peng Z; Sheng C; Kim M; Yap PT; Wee CY; Shen D
    Neuroinformatics; 2020 Jan; 18(1):1-24. PubMed ID: 30982183
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Sub-Network Kernels for Measuring Similarity of Brain Connectivity Networks in Disease Diagnosis.
    Jie B; Liu M; Zhang D; Shen D
    IEEE Trans Image Process; 2018 May; 27(5):2340-2353. PubMed ID: 29470170
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Hi-GCN: A hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction.
    Jiang H; Cao P; Xu M; Yang J; Zaiane O
    Comput Biol Med; 2020 Dec; 127():104096. PubMed ID: 33166800
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Classification of Alzheimer's Disease Using Whole Brain Hierarchical Network.
    Liu J; Li M; Lan W; Wu FX; Pan Y; Wang J
    IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(2):624-632. PubMed ID: 28114031
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease.
    Spasov S; Passamonti L; Duggento A; Liò P; Toschi N;
    Neuroimage; 2019 Apr; 189():276-287. PubMed ID: 30654174
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Temporal and Spatial Analysis of Alzheimer's Disease Based on an Improved Convolutional Neural Network and a Resting-State FMRI Brain Functional Network.
    Sun H; Wang A; He S
    Int J Environ Res Public Health; 2022 Apr; 19(8):. PubMed ID: 35457373
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Discriminative Sparse Features for Alzheimer's Disease Diagnosis Using Multimodal Image Data.
    Ortiz A; Lozano F; Gorriz JM; Ramirez J; Martinez Murcia FJ;
    Curr Alzheimer Res; 2018; 15(1):67-79. PubMed ID: 28934923
    [TBL] [Abstract][Full Text] [Related]  

  • 37. MVS-GCN: A prior brain structure learning-guided multi-view graph convolution network for autism spectrum disorder diagnosis.
    Wen G; Cao P; Bao H; Yang W; Zheng T; Zaiane O
    Comput Biol Med; 2022 Mar; 142():105239. PubMed ID: 35066446
    [TBL] [Abstract][Full Text] [Related]  

  • 38. A Novel Grading Biomarker for the Prediction of Conversion From Mild Cognitive Impairment to Alzheimer's Disease.
    Tong T; Gao Q; Guerrero R; Ledig C; Chen L; Rueckert D; Initiative ADN
    IEEE Trans Biomed Eng; 2017 Jan; 64(1):155-165. PubMed ID: 27046891
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Region-of-Interest based sparse feature learning method for Alzheimer's disease identification.
    Wang L; Liu Y; Zeng X; Cheng H; Wang Z; Wang Q
    Comput Methods Programs Biomed; 2020 Apr; 187():105290. PubMed ID: 31927305
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Multiview Feature Learning With Multiatlas-Based Functional Connectivity Networks for MCI Diagnosis.
    Zhang Y; Zhang H; Adeli E; Chen X; Liu M; Shen D
    IEEE Trans Cybern; 2022 Jul; 52(7):6822-6833. PubMed ID: 33306476
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 11.