BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

293 related articles for article (PubMed ID: 33251178)

  • 1. Alzheimer's Disease Classification With a Cascade Neural Network.
    You Z; Zeng R; Lan X; Ren H; You Z; Shi X; Zhao S; Guo Y; Jiang X; Hu X
    Front Public Health; 2020; 8():584387. PubMed ID: 33251178
    [TBL] [Abstract][Full Text] [Related]  

  • 2. An improved I-FAST system for the diagnosis of Alzheimer's disease from unprocessed electroencephalograms by using robust invariant features.
    Buscema M; Vernieri F; Massini G; Scrascia F; Breda M; Rossini PM; Grossi E
    Artif Intell Med; 2015 May; 64(1):59-74. PubMed ID: 25997573
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Diagnosis of Alzheimer's disease and Mild Cognitive Impairment using EEG and Recurrent Neural Networks.
    Gkenios G; Latsiou K; Diamantaras K; Chouvarda I; Tsolaki M
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():3179-3182. PubMed ID: 36086481
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Lacsogram: A New EEG Tool to Diagnose Alzheimer's Disease.
    Rodrigues PM; Bispo BC; Garrett C; Alves D; Teixeira JP; Freitas D
    IEEE J Biomed Health Inform; 2021 Sep; 25(9):3384-3395. PubMed ID: 33784628
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Complexity of EEG Dynamics for Early Diagnosis of Alzheimer's Disease Using Permutation Entropy Neuromarker.
    Şeker M; Özbek Y; Yener G; Özerdem MS
    Comput Methods Programs Biomed; 2021 Jul; 206():106116. PubMed ID: 33957376
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Detection of Early Stage Alzheimer's Disease using EEG Relative Power with Deep Neural Network.
    Kim D; Kim K
    Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():352-355. PubMed ID: 30440409
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Combining EEG signal processing with supervised methods for Alzheimer's patients classification.
    Fiscon G; Weitschek E; Cialini A; Felici G; Bertolazzi P; De Salvo S; Bramanti A; Bramanti P; De Cola MC
    BMC Med Inform Decis Mak; 2018 May; 18(1):35. PubMed ID: 29855305
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Multi-Modal Classification Method for Early Diagnosis of Mild Cognitive Impairment and Alzheimer's Disease Using Three Paradigms With Various Task Difficulties.
    Chen S; Zhang C; Yang H; Peng L; Xie H; Lv Z; Hou ZG
    IEEE Trans Neural Syst Rehabil Eng; 2024; 32():1477-1486. PubMed ID: 38568773
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep insights into MCI diagnosis: A comparative deep learning analysis of EEG time series.
    Şeker M; Özerdem MS
    J Neurosci Methods; 2024 Mar; 403():110057. PubMed ID: 38215948
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The I.F.A.S.T. model allows the prediction of conversion to Alzheimer disease in patients with mild cognitive impairment with high degree of accuracy.
    Buscema M; Grossi E; Capriotti M; Babiloni C; Rossini P
    Curr Alzheimer Res; 2010 Mar; 7(2):173-87. PubMed ID: 19860726
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Application of advanced machine learning methods on resting-state fMRI network for identification of mild cognitive impairment and Alzheimer's disease.
    Khazaee A; Ebrahimzadeh A; Babajani-Feremi A
    Brain Imaging Behav; 2016 Sep; 10(3):799-817. PubMed ID: 26363784
    [TBL] [Abstract][Full Text] [Related]  

  • 13. The IFAST model, a novel parallel nonlinear EEG analysis technique, distinguishes mild cognitive impairment and Alzheimer's disease patients with high degree of accuracy.
    Buscema M; Rossini P; Babiloni C; Grossi E
    Artif Intell Med; 2007 Jun; 40(2):127-41. PubMed ID: 17466496
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Spatio-Temporal Fluctuations of Neural Dynamics in Mild Cognitive Impairment and Alzheimer's Disease.
    Poza J; Gómez C; García M; Tola-Arribas MA; Carreres A; Cano M; Hornero R
    Curr Alzheimer Res; 2017; 14(9):924-936. PubMed ID: 28290246
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Early diagnosis of mild cognitive impairment and Alzheimer's with event-related potentials and event-related desynchronization in N-back working memory tasks.
    Fraga FJ; Mamani GQ; Johns E; Tavares G; Falk TH; Phillips NA
    Comput Methods Programs Biomed; 2018 Oct; 164():1-13. PubMed ID: 30195417
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. RNN-based longitudinal analysis for diagnosis of Alzheimer's disease.
    Cui R; Liu M;
    Comput Med Imaging Graph; 2019 Apr; 73():1-10. PubMed ID: 30763637
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia.
    Ieracitano C; Mammone N; Hussain A; Morabito FC
    Neural Netw; 2020 Mar; 123():176-190. PubMed ID: 31884180
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Neural biomarker diagnosis and prediction to mild cognitive impairment and Alzheimer's disease using EEG technology.
    Jiao B; Li R; Zhou H; Qing K; Liu H; Pan H; Lei Y; Fu W; Wang X; Xiao X; Liu X; Yang Q; Liao X; Zhou Y; Fang L; Dong Y; Yang Y; Jiang H; Huang S; Shen L
    Alzheimers Res Ther; 2023 Feb; 15(1):32. PubMed ID: 36765411
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An explainable Artificial Intelligence approach to study MCI to AD conversion via HD-EEG processing.
    Morabito FC; Ieracitano C; Mammone N
    Clin EEG Neurosci; 2023 Jan; 54(1):51-60. PubMed ID: 34889152
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.