BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1555 related articles for article (PubMed ID: 32896633)

  • 1. fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations.
    Vu H; Kim HC; Jung M; Lee JH
    Neuroimage; 2020 Dec; 223():117328. PubMed ID: 32896633
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.
    Jang H; Plis SM; Calhoun VD; Lee JH
    Neuroimage; 2017 Jan; 145(Pt B):314-328. PubMed ID: 27079534
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A Multichannel 2D Convolutional Neural Network Model for Task-Evoked fMRI Data Classification.
    Hu J; Kuang Y; Liao B; Cao L; Dong S; Li P
    Comput Intell Neurosci; 2019; 2019():5065214. PubMed ID: 32082370
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Classification of schizophrenia and normal controls using 3D convolutional neural network and outcome visualization.
    Oh K; Kim W; Shen G; Piao Y; Kang NI; Oh IS; Chung YC
    Schizophr Res; 2019 Oct; 212():186-195. PubMed ID: 31395487
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep neural network predicts emotional responses of the human brain from functional magnetic resonance imaging.
    Kim HC; Bandettini PA; Lee JH
    Neuroimage; 2019 Feb; 186():607-627. PubMed ID: 30366076
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization.
    Zhao Y; Ge F; Liu T
    Med Image Anal; 2018 Jul; 47():111-126. PubMed ID: 29705574
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 3D-Deep Learning Based Automatic Diagnosis of Alzheimer's Disease with Joint MMSE Prediction Using Resting-State fMRI.
    Duc NT; Ryu S; Qureshi MNI; Choi M; Lee KH; Lee B
    Neuroinformatics; 2020 Jan; 18(1):71-86. PubMed ID: 31093956
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Decoding fMRI data with support vector machines and deep neural networks.
    Liang Y; Bo K; Meyyappan S; Ding M
    J Neurosci Methods; 2024 Jan; 401():110004. PubMed ID: 37914001
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep convolutional neural network based hyperspectral brain tissue classification.
    Poonkuzhali P; Helen Prabha K
    J Xray Sci Technol; 2023; 31(4):777-796. PubMed ID: 37182861
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Transfer learning of deep neural network representations for fMRI decoding.
    Svanera M; Savardi M; Benini S; Signoroni A; Raz G; Hendler T; Muckli L; Goebel R; Valente G
    J Neurosci Methods; 2019 Dec; 328():108319. PubMed ID: 31585315
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Spatially regularized machine learning for task and resting-state fMRI.
    Song X; Panych LP; Chen NK
    J Neurosci Methods; 2016 Jan; 257():214-28. PubMed ID: 26470627
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks.
    Alawad M; Gao S; Qiu JX; Yoon HJ; Blair Christian J; Penberthy L; Mumphrey B; Wu XC; Coyle L; Tourassi G
    J Am Med Inform Assoc; 2020 Jan; 27(1):89-98. PubMed ID: 31710668
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Convolutional neural networks for decoding of covert attention focus and saliency maps for EEG feature visualization.
    Farahat A; Reichert C; Sweeney-Reed CM; Hinrichs H
    J Neural Eng; 2019 Oct; 16(6):066010. PubMed ID: 31416059
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Decoding and mapping task states of the human brain via deep learning.
    Wang X; Liang X; Jiang Z; Nguchu BA; Zhou Y; Wang Y; Wang H; Li Y; Zhu Y; Wu F; Gao JH; Qiu B
    Hum Brain Mapp; 2020 Apr; 41(6):1505-1519. PubMed ID: 31816152
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Discriminative analysis of schizophrenia patients using an integrated model combining 3D CNN with 2D CNN: A multimodal MR image and connectomics analysis.
    Guo H; Jian S; Zhou Y; Chen X; Chen J; Zhou J; Huang Y; Ma G; Li X; Ning Y; Wu F; Wu K
    Brain Res Bull; 2024 Jan; 206():110846. PubMed ID: 38104672
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.
    Kim J; Calhoun VD; Shim E; Lee JH
    Neuroimage; 2016 Jan; 124(Pt A):127-146. PubMed ID: 25987366
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics.
    He T; Kong R; Holmes AJ; Nguyen M; Sabuncu MR; Eickhoff SB; Bzdok D; Feng J; Yeo BTT
    Neuroimage; 2020 Feb; 206():116276. PubMed ID: 31610298
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Brain decoding of the Human Connectome Project tasks in a dense individual fMRI dataset.
    Rastegarnia S; St-Laurent M; DuPre E; Pinsard B; Bellec P
    Neuroimage; 2023 Dec; 283():120395. PubMed ID: 37832707
    [TBL] [Abstract][Full Text] [Related]  

  • 19. MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques.
    Saeedi S; Rezayi S; Keshavarz H; R Niakan Kalhori S
    BMC Med Inform Decis Mak; 2023 Jan; 23(1):16. PubMed ID: 36691030
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Automated Identification of Hookahs (Waterpipes) on Instagram: An Application in Feature Extraction Using Convolutional Neural Network and Support Vector Machine Classification.
    Zhang Y; Allem JP; Unger JB; Boley Cruz T
    J Med Internet Res; 2018 Nov; 20(11):e10513. PubMed ID: 30452385
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 78.