BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

173 related articles for article (PubMed ID: 32791440)

  • 1. Classification of ADHD with fMRI data and multi-objective optimization.
    Shao L; You Y; Du H; Fu D
    Comput Methods Programs Biomed; 2020 Nov; 196():105676. PubMed ID: 32791440
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Classification of ADHD with bi-objective optimization.
    Shao L; Xu Y; Fu D
    J Biomed Inform; 2018 Aug; 84():164-170. PubMed ID: 30009990
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Fusion of fMRI and non-imaging data for ADHD classification.
    Riaz A; Asad M; Alonso E; Slabaugh G
    Comput Med Imaging Graph; 2018 Apr; 65():115-128. PubMed ID: 29137838
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study.
    Qureshi MN; Min B; Jo HJ; Lee B
    PLoS One; 2016; 11(8):e0160697. PubMed ID: 27500640
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Multimodal neuroimaging-based prediction of adult outcomes in childhood-onset ADHD using ensemble learning techniques.
    Luo Y; Alvarez TL; Halperin JM; Li X
    Neuroimage Clin; 2020; 26():102238. PubMed ID: 32182578
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Inverse free reduced universum twin support vector machine for imbalanced data classification.
    Moosaei H; Ganaie MA; Hladík M; Tanveer M
    Neural Netw; 2023 Jan; 157():125-135. PubMed ID: 36334534
    [TBL] [Abstract][Full Text] [Related]  

  • 7. DeepFMRI: End-to-end deep learning for functional connectivity and classification of ADHD using fMRI.
    Riaz A; Asad M; Alonso E; Slabaugh G
    J Neurosci Methods; 2020 Apr; 335():108506. PubMed ID: 32001294
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Extreme learning machine-based classification of ADHD using brain structural MRI data.
    Peng X; Lin P; Zhang T; Wang J
    PLoS One; 2013; 8(11):e79476. PubMed ID: 24260229
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Hyper-connectivity of functional networks for brain disease diagnosis.
    Jie B; Wee CY; Shen D; Zhang D
    Med Image Anal; 2016 Aug; 32():84-100. PubMed ID: 27060621
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Using Functional or Structural Magnetic Resonance Images and Personal Characteristic Data to Identify ADHD and Autism.
    Ghiassian S; Greiner R; Jin P; Brown MR
    PLoS One; 2016; 11(12):e0166934. PubMed ID: 28030565
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Attributed graph distance measure for automatic detection of attention deficit hyperactive disordered subjects.
    Dey S; Rao AR; Shah M
    Front Neural Circuits; 2014; 8():64. PubMed ID: 24982615
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Connectivity Analysis and Feature Classification in Attention Deficit Hyperactivity Disorder Sub-Types: A Task Functional Magnetic Resonance Imaging Study.
    Park BY; Kim M; Seo J; Lee JM; Park H
    Brain Topogr; 2016 May; 29(3):429-39. PubMed ID: 26602102
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A general prediction model for the detection of ADHD and Autism using structural and functional MRI.
    Sen B; Borle NC; Greiner R; Brown MRG
    PLoS One; 2018; 13(4):e0194856. PubMed ID: 29664902
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Analysis of structural brain MRI and multi-parameter classification for Alzheimer's disease.
    Zhang Y; Liu S
    Biomed Tech (Berl); 2018 Jul; 63(4):427-437. PubMed ID: 28622141
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Metaheuristic Spatial Transformation (MST) for accurate detection of Attention Deficit Hyperactivity Disorder (ADHD) using rs-fMRI.
    Aradhya AMS; Sundaram S; Pratama M
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():2829-2832. PubMed ID: 33018595
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Network-based classification of ADHD patients using discriminative subnetwork selection and graph kernel PCA.
    Du J; Wang L; Jie B; Zhang D
    Comput Med Imaging Graph; 2016 Sep; 52():82-88. PubMed ID: 27166430
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Imbalanced learning: Improving classification of diabetic neuropathy from magnetic resonance imaging.
    Teh K; Armitage P; Tesfaye S; Selvarajah D; Wilkinson ID
    PLoS One; 2020; 15(12):e0243907. PubMed ID: 33320890
    [TBL] [Abstract][Full Text] [Related]  

  • 18. ADHD diagnosis using structural brain MRI and personal characteristic data with machine learning framework.
    Lohani DC; Rana B
    Psychiatry Res Neuroimaging; 2023 Sep; 334():111689. PubMed ID: 37536046
    [TBL] [Abstract][Full Text] [Related]  

  • 19. ADHD classification by dual subspace learning using resting-state functional connectivity.
    Chen Y; Tang Y; Wang C; Liu X; Zhao L; Wang Z
    Artif Intell Med; 2020 Mar; 103():101786. PubMed ID: 32143793
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Efficient Selection of Gaussian Kernel SVM Parameters for Imbalanced Data.
    Tsai CA; Chang YJ
    Genes (Basel); 2023 Feb; 14(3):. PubMed ID: 36980852
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.