148 related articles for article (PubMed ID: 33383465)
1. A New dispersion entropy and fuzzy logic system methodology for automated classification of dementia stages using electroencephalograms.
Amezquita-Sanchez JP; Mammone N; Morabito FC; Adeli H
Clin Neurol Neurosurg; 2021 Feb; 201():106446. PubMed ID: 33383465
[TBL] [Abstract][Full Text] [Related]
2. A novel methodology for automated differential diagnosis of mild cognitive impairment and the Alzheimer's disease using EEG signals.
Amezquita-Sanchez JP; Mammone N; Morabito FC; Marino S; Adeli H
J Neurosci Methods; 2019 Jul; 322():88-95. PubMed ID: 31055026
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Diagnosis of Alzheimer's disease with Electroencephalography in a differential framework.
Houmani N; Vialatte F; Gallego-Jutglà E; Dreyfus G; Nguyen-Michel VH; Mariani J; Kinugawa K
PLoS One; 2018; 13(3):e0193607. PubMed ID: 29558517
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Discrimination of mild cognitive impairment and Alzheimer's disease using transfer entropy measures of scalp EEG.
McBride J; Zhao X; Munro N; Jicha G; Smith C; Jiang Y
J Healthc Eng; 2015; 6(1):55-70. PubMed ID: 25708377
[TBL] [Abstract][Full Text] [Related]
7. A combination of 3-D discrete wavelet transform and 3-D local binary pattern for classification of mild cognitive impairment.
Bhasin H; Agrawal RK;
BMC Med Inform Decis Mak; 2020 Feb; 20(1):37. PubMed ID: 32085774
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Discrimination of stroke-related mild cognitive impairment and vascular dementia using EEG signal analysis.
Al-Qazzaz NK; Ali SHBM; Ahmad SA; Islam MS; Escudero J
Med Biol Eng Comput; 2018 Jan; 56(1):137-157. PubMed ID: 29119540
[TBL] [Abstract][Full Text] [Related]
10. A fuzzy-based system reveals Alzheimer's Disease onset in subjects with Mild Cognitive Impairment.
Tangaro S; Fanizzi A; Amoroso N; Bellotti R;
Phys Med; 2017 Jun; 38():36-44. PubMed ID: 28610695
[TBL] [Abstract][Full Text] [Related]
11. Multi-Feature Fusion Method Based on EEG Signal and its Application in Stroke Classification.
Li F; Fan Y; Zhang X; Wang C; Hu F; Jia W; Hui H
J Med Syst; 2019 Dec; 44(2):39. PubMed ID: 31865469
[TBL] [Abstract][Full Text] [Related]
12. Characterization of complexity in the electroencephalograph activity of Alzheimer's disease based on fuzzy entropy.
Cao Y; Cai L; Wang J; Wang R; Yu H; Cao Y; Liu J
Chaos; 2015 Aug; 25(8):083116. PubMed ID: 26328567
[TBL] [Abstract][Full Text] [Related]
13. A hybrid feature selection approach for the early diagnosis of Alzheimer's disease.
Gallego-Jutglà E; Solé-Casals J; Vialatte FB; Elgendi M; Cichocki A; Dauwels J
J Neural Eng; 2015 Feb; 12(1):016018. PubMed ID: 25605667
[TBL] [Abstract][Full Text] [Related]
14. Assessment and Comparison of Nonlinear Measures in Resting-State Magnetoencephalograms in Alzheimer's Disease and Mild Cognitive Impairment.
Azami H; Daftarifard E; Humeau-Heurtier A; Fernandez A; Abasolo D; Rajji TK
J Alzheimers Dis; 2023; 96(3):1151-1162. PubMed ID: 37980661
[TBL] [Abstract][Full Text] [Related]
15. MRI based automated diagnosis of Alzheimer's: Fusing 3D wavelet-features with clinical data.
Ayaz A; Ahmad MZ; Khurshid K; Kamboh AM
Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():1210-1213. PubMed ID: 29060093
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Diagnostic differentiation of mild cognitive impairment due to Alzheimer's disease using a hippocampus-dependent test of spatial memory.
Moodley K; Minati L; Contarino V; Prioni S; Wood R; Cooper R; D'Incerti L; Tagliavini F; Chan D
Hippocampus; 2015 Aug; 25(8):939-51. PubMed ID: 25605659
[TBL] [Abstract][Full Text] [Related]
18. Research of the characteristics of Alzheimer's disease using EEG.
Ueda T; Musha T; Yagi T
Annu Int Conf IEEE Eng Med Biol Soc; 2009; 2009():4998-5001. PubMed ID: 19965030
[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. An EEG-Based Fuzzy Probability Model for Early Diagnosis of Alzheimer's Disease.
Chiang HS; Pao SC
J Med Syst; 2016 May; 40(5):125. PubMed ID: 27059738
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
