BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

46 related articles for article (PubMed ID: 35205506)

  • 1. Using Electroencephalogram-Extracted Nonlinear Complexity and Wavelet-Extracted Power Rhythm Features during the Performance of Demanding Cognitive Tasks (Aristotle's Syllogisms) in Optimally Classifying Patients with Anorexia Nervosa.
    Karavia A; Papaioannou A; Michopoulos I; Papageorgiou PC; Papaioannou G; Gonidakis F; Papageorgiou CC
    Brain Sci; 2024 Mar; 14(3):. PubMed ID: 38539639
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Multiple characteristics analysis of Alzheimer's electroencephalogram by power spectral density and Lempel-Ziv complexity.
    Liu X; Zhang C; Ji Z; Ma Y; Shang X; Zhang Q; Zheng W; Li X; Gao J; Wang R; Wang J; Yu H
    Cogn Neurodyn; 2016 Apr; 10(2):121-33. PubMed ID: 27066150
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Depression assessment using integrated multi-featured EEG bands deep neural network models: Leveraging ensemble learning techniques.
    Chung KH; Chang YS; Yen WT; Lin L; Abimannan S
    Comput Struct Biotechnol J; 2024 Dec; 23():1450-1468. PubMed ID: 38623563
    [TBL] [Abstract][Full Text] [Related]  

  • 4. FC-TFS-CGRU: A Temporal-Frequency-Spatial Electroencephalography Emotion Recognition Model Based on Functional Connectivity and a Convolutional Gated Recurrent Unit Hybrid Architecture.
    Wu X; Zhang Y; Li J; Yang H; Wu X
    Sensors (Basel); 2024 Mar; 24(6):. PubMed ID: 38544241
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A machine learning based depression screening framework using temporal domain features of the electroencephalography signals.
    Khan S; Umar Saeed SM; Frnda J; Arsalan A; Amin R; Gantassi R; Noorani SH
    PLoS One; 2024; 19(3):e0299127. PubMed ID: 38536782
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Fractal Analysis of Electrophysiological Signals to Detect and Monitor Depression: What We Know So Far?
    Čukić M; Olejarzcyk E; Bachmann M
    Adv Neurobiol; 2024; 36():677-692. PubMed ID: 38468058
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Clinical Sensitivity of Fractal Neurodynamics.
    Olejarczyk E; Cukic M; Porcaro C; Zappasodi F; Tecchio F
    Adv Neurobiol; 2024; 36():285-312. PubMed ID: 38468039
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Multimodal Approach for Pilot Mental State Detection Based on EEG.
    Alreshidi I; Moulitsas I; Jenkins KW
    Sensors (Basel); 2023 Aug; 23(17):. PubMed ID: 37687804
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Neurosteroids: mechanistic considerations and clinical prospects.
    Maguire JL; Mennerick S
    Neuropsychopharmacology; 2024 Jan; 49(1):73-82. PubMed ID: 37369775
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine Learning Model for Computer-Aided Depression Screening among Young Adults Using Wireless EEG Headset.
    Sakib N; Islam MK; Faruk T
    Comput Intell Neurosci; 2023; 2023():1701429. PubMed ID: 37293375
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Towards Context-Aware Facial Emotion Reaction Database for Dyadic Interaction Settings.
    Sham AH; Khan A; Lamas D; Tikka P; Anbarjafari G
    Sensors (Basel); 2023 Jan; 23(1):. PubMed ID: 36617055
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automated recognition of major depressive disorder from cardiovascular and respiratory physiological signals.
    Zitouni MS; Lih Oh S; Vicnesh J; Khandoker A; Acharya UR
    Front Psychiatry; 2022; 13():970993. PubMed ID: 36569627
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Few-Electrode EEG from the Wearable Devices Using Domain Adaptation for Depression Detection.
    Wu W; Ma L; Lian B; Cai W; Zhao X
    Biosensors (Basel); 2022 Nov; 12(12):. PubMed ID: 36551054
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning approaches for diagnosing depression using EEG: A review.
    Liu Y; Pu C; Xia S; Deng D; Wang X; Li M
    Transl Neurosci; 2022 Jan; 13(1):224-235. PubMed ID: 36045698
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A novel EEG-based major depressive disorder detection framework with two-stage feature selection.
    Li Y; Shen Y; Fan X; Huang X; Yu H; Zhao G; Ma W
    BMC Med Inform Decis Mak; 2022 Aug; 22(1):209. PubMed ID: 35933348
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Ungulate Detection and Species Classification from Camera Trap Images Using RetinaNet and Faster R-CNN.
    Vecvanags A; Aktas K; Pavlovs I; Avots E; Filipovs J; Brauns A; Done G; Jakovels D; Anbarjafari G
    Entropy (Basel); 2022 Feb; 24(3):. PubMed ID: 35327863
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Prediction of sgRNA Off-Target Activity in CRISPR/Cas9 Gene Editing Using Graph Convolution Network.
    Vinodkumar PK; Ozcinar C; Anbarjafari G
    Entropy (Basel); 2021 May; 23(5):. PubMed ID: 34069050
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Ensemble Approach for Detection of Depression Using EEG Features.
    Avots E; Jermakovs K; Bachmann M; Päeske L; Ozcinar C; Anbarjafari G
    Entropy (Basel); 2022 Jan; 24(2):. PubMed ID: 35205506
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Methods for classifying depression in single channel EEG using linear and nonlinear signal analysis.
    Bachmann M; Päeske L; Kalev K; Aarma K; Lehtmets A; Ööpik P; Lass J; Hinrikus H
    Comput Methods Programs Biomed; 2018 Mar; 155():11-17. PubMed ID: 29512491
    [TBL] [Abstract][Full Text] [Related]  

  • 20.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 3.