These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

259 related articles for article (PubMed ID: 33547343)

  • 1. Multimodal deep learning models for early detection of Alzheimer's disease stage.
    Venugopalan J; Tong L; Hassanzadeh HR; Wang MD
    Sci Rep; 2021 Feb; 11(1):3254. PubMed ID: 33547343
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. A Deep Learning Approach for Automated Diagnosis and Multi-Class Classification of Alzheimer's Disease Stages Using Resting-State fMRI and Residual Neural Networks.
    Ramzan F; Khan MUG; Rehmat A; Iqbal S; Saba T; Rehman A; Mehmood Z
    J Med Syst; 2019 Dec; 44(2):37. PubMed ID: 31853655
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automated MRI-Based Deep Learning Model for Detection of Alzheimer's Disease Process.
    Feng W; Halm-Lutterodt NV; Tang H; Mecum A; Mesregah MK; Ma Y; Li H; Zhang F; Wu Z; Yao E; Guo X
    Int J Neural Syst; 2020 Jun; 30(6):2050032. PubMed ID: 32498641
    [TBL] [Abstract][Full Text] [Related]  

  • 5. c-Diadem: a constrained dual-input deep learning model to identify novel biomarkers in Alzheimer's disease.
    Jemimah S; AlShehhi A;
    BMC Med Genomics; 2023 Oct; 16(Suppl 2):244. PubMed ID: 37833700
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease.
    Liu M; Li F; Yan H; Wang K; Ma Y; ; Shen L; Xu M
    Neuroimage; 2020 Mar; 208():116459. PubMed ID: 31837471
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.
    Liu M; Cheng D; Wang K; Wang Y;
    Neuroinformatics; 2018 Oct; 16(3-4):295-308. PubMed ID: 29572601
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Alzheimer's disease diagnosis framework from incomplete multimodal data using convolutional neural networks.
    Abdelaziz M; Wang T; Elazab A
    J Biomed Inform; 2021 Sep; 121():103863. PubMed ID: 34229061
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep Learning for Alzheimer's Disease Classification using Texture Features.
    So JH; Madusanka N; Choi HK; Choi BK; Park HG
    Curr Med Imaging Rev; 2019; 15(7):689-698. PubMed ID: 32008517
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Optimizing Machine Learning Methods to Improve Predictive Models of Alzheimer's Disease.
    Ezzati A; Zammit AR; Harvey DJ; Habeck C; Hall CB; Lipton RB;
    J Alzheimers Dis; 2019; 71(3):1027-1036. PubMed ID: 31476152
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Hippocampal shape and asymmetry analysis by cascaded convolutional neural networks for Alzheimer's disease diagnosis.
    Li A; Li F; Elahifasaee F; Liu M; Zhang L;
    Brain Imaging Behav; 2021 Oct; 15(5):2330-2339. PubMed ID: 33398778
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Alzheimer's disease diagnosis from diffusion tensor images using convolutional neural networks.
    Marzban EN; Eldeib AM; Yassine IA; Kadah YM;
    PLoS One; 2020; 15(3):e0230409. PubMed ID: 32208428
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer's disease patients: From the alzheimer's disease neuroimaging initiative (ADNI) database.
    Dimitriadis SI; Liparas D; Tsolaki MN;
    J Neurosci Methods; 2018 May; 302():14-23. PubMed ID: 29269320
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks.
    Basaia S; Agosta F; Wagner L; Canu E; Magnani G; Santangelo R; Filippi M;
    Neuroimage Clin; 2019; 21():101645. PubMed ID: 30584016
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Effective feature learning and fusion of multimodality data using stage-wise deep neural network for dementia diagnosis.
    Zhou T; Thung KH; Zhu X; Shen D
    Hum Brain Mapp; 2019 Feb; 40(3):1001-1016. PubMed ID: 30381863
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease.
    Hao X; Bao Y; Guo Y; Yu M; Zhang D; Risacher SL; Saykin AJ; Yao X; Shen L;
    Med Image Anal; 2020 Feb; 60():101625. PubMed ID: 31841947
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Multi-modality MRI for Alzheimer's disease detection using deep learning.
    Houria L; Belkhamsa N; Cherfa A; Cherfa Y
    Phys Eng Sci Med; 2022 Dec; 45(4):1043-1053. PubMed ID: 36063346
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Diagnostic accuracy study of automated stratification of Alzheimer's disease and mild cognitive impairment via deep learning based on MRI.
    Chen X; Tang M; Liu A; Wei X
    Ann Transl Med; 2022 Jul; 10(14):765. PubMed ID: 35965800
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Multi-modality sparse representation-based classification for Alzheimer's disease and mild cognitive impairment.
    Xu L; Wu X; Chen K; Yao L
    Comput Methods Programs Biomed; 2015 Nov; 122(2):182-90. PubMed ID: 26298855
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Early diagnosis of Alzheimer's disease using combined features from voxel-based morphometry and cortical, subcortical, and hippocampus regions of MRI T1 brain images.
    Gupta Y; Lee KH; Choi KY; Lee JJ; Kim BC; Kwon GR; ;
    PLoS One; 2019; 14(10):e0222446. PubMed ID: 31584953
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.