BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

188 related articles for article (PubMed ID: 34439759)

  • 1. A Novel Knowledge Distillation-Based Feature Selection for the Classification of ADHD.
    Khan NA; Waheeb SA; Riaz A; Shang X
    Biomolecules; 2021 Jul; 11(8):. PubMed ID: 34439759
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Discriminating ADHD From Healthy Controls Using a Novel Feature Selection Method Based on Relative Importance and Ensemble Learning.
    Yao D; Guo X; Zhao Q; Liu L; Cao Q; Wang Y; D Calhoun V; Sun L; Sui J
    Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():4632-4635. PubMed ID: 30441383
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A Three-Stage Teacher, Student Neural Networks and Sequential Feed Forward Selection-Based Feature Selection Approach for the Classification of Autism Spectrum Disorder.
    Khan NA; Waheeb SA; Riaz A; Shang X
    Brain Sci; 2020 Oct; 10(10):. PubMed ID: 33086634
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data.
    Deshpande G; Wang P; Rangaprakash D; Wilamowski B
    IEEE Trans Cybern; 2015 Dec; 45(12):2668-79. PubMed ID: 25576588
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Classification of drug-naive children with attention-deficit/hyperactivity disorder from typical development controls using resting-state fMRI and graph theoretical approach.
    Rezaei M; Zare H; Hakimdavoodi H; Nasseri S; Hebrani P
    Front Hum Neurosci; 2022; 16():948706. PubMed ID: 36061501
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Machine Learning Techniques for the Diagnosis of Attention-Deficit/Hyperactivity Disorder from Magnetic Resonance Imaging: A Concise Review.
    Periyasamy R; Vibashan VS; Varghese GT; Aleem MA
    Neurol India; 2021; 69(6):1518-1523. PubMed ID: 34979636
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. 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]  

  • 10. 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]  

  • 11. 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]  

  • 12. Altered temporal features of intrinsic connectivity networks in boys with combined type of attention deficit hyperactivity disorder.
    Wang XH; Li L
    Eur J Radiol; 2015 May; 84(5):947-54. PubMed ID: 25795197
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Attention Deficit Hyperactivity Disorder Classification Based on Deep Learning.
    Wang D; Hong D; Wu Q
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(2):1581-1586. PubMed ID: 35471884
    [TBL] [Abstract][Full Text] [Related]  

  • 14. BrainNET: Inference of Brain Network Topology Using Machine Learning.
    Murugesan GK; Ganesh C; Nalawade S; Davenport EM; Wagner B; Kim WH; Maldjian JA
    Brain Connect; 2020 Oct; 10(8):422-435. PubMed ID: 33030350
    [No Abstract]   [Full Text] [Related]  

  • 15. Learning a Phenotypic-Attribute Attentional Brain Connectivity Embedding for ADHD Classification using rs-fMRI.
    Gao MS; Tsai FS; Lee CC
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():5472-5475. PubMed ID: 33019218
    [TBL] [Abstract][Full Text] [Related]  

  • 16. ADHD diagnosis guided by functional brain networks combined with domain knowledge.
    Cao C; Fu H; Li G; Wang M; Gao X
    Comput Biol Med; 2024 Jul; 177():108611. PubMed ID: 38788375
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Hyperactivity/restlessness is associated with increased functional connectivity in adults with ADHD: a dimensional analysis of resting state fMRI.
    Sörös P; Hoxhaj E; Borel P; Sadohara C; Feige B; Matthies S; Müller HHO; Bachmann K; Schulze M; Philipsen A
    BMC Psychiatry; 2019 Jan; 19(1):43. PubMed ID: 30683074
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Abnormal brain connectivity patterns in adults with ADHD: a coherence study.
    Sato JR; Hoexter MQ; Castellanos XF; Rohde LA
    PLoS One; 2012; 7(9):e45671. PubMed ID: 23049834
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Altered regional homogeneity patterns in adults with attention-deficit hyperactivity disorder.
    Wang X; Jiao Y; Tang T; Wang H; Lu Z
    Eur J Radiol; 2013 Sep; 82(9):1552-7. PubMed ID: 23684384
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.