BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

177 related articles for article (PubMed ID: 36138933)

  • 1. Automatic Recognition of High-Density Epileptic EEG Using Support Vector Machine and Gradient-Boosting Decision Tree.
    He J; Yang L; Liu D; Song Z
    Brain Sci; 2022 Sep; 12(9):. PubMed ID: 36138933
    [TBL] [Abstract][Full Text] [Related]  

  • 2. EEG-Driven Prediction Model of Oxcarbazepine Treatment Outcomes in Patients With Newly-Diagnosed Focal Epilepsy.
    Wang B; Han X; Zhao Z; Wang N; Zhao P; Li M; Zhang Y; Zhao T; Chen Y; Ren Z; Hong Y
    Front Med (Lausanne); 2021; 8():781937. PubMed ID: 35047529
    [No Abstract]   [Full Text] [Related]  

  • 3. EEG Microstate Features as an Automatic Recognition Model of High-Density Epileptic EEG Using Support Vector Machine.
    Yang L; He J; Liu D; Zheng W; Song Z
    Brain Sci; 2022 Dec; 12(12):. PubMed ID: 36552190
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Grasshopper optimization algorithm-based approach for the optimization of ensemble classifier and feature selection to classify epileptic EEG signals.
    Singh G; Singh B; Kaur M
    Med Biol Eng Comput; 2019 Jun; 57(6):1323-1339. PubMed ID: 30756231
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Automatic identification of epileptic seizures using volume of phase space representation.
    Krishnaprasanna R; Vijaya Baskar V; Panneerselvam J
    Phys Eng Sci Med; 2021 Jun; 44(2):545-556. PubMed ID: 33956327
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Epileptic Patient Activity Recognition System Using Extreme Learning Machine Method.
    Ayman U; Zia MS; Okon OD; Rehman NU; Meraj T; Ragab AE; Rauf HT
    Biomedicines; 2023 Mar; 11(3):. PubMed ID: 36979795
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automated Detection of Driver Fatigue Based on AdaBoost Classifier with EEG Signals.
    Hu J
    Front Comput Neurosci; 2017; 11():72. PubMed ID: 28824409
    [No Abstract]   [Full Text] [Related]  

  • 8. Epileptic seizure classifications using empirical mode decomposition and its derivative.
    Karabiber Cura O; Kocaaslan Atli S; Türe HS; Akan A
    Biomed Eng Online; 2020 Feb; 19(1):10. PubMed ID: 32059668
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Automated FBSE-EWT based learning framework for detection of epileptic seizures using time-segmented EEG signals.
    Anuragi A; Sisodia DS; Pachori RB
    Comput Biol Med; 2021 Sep; 136():104708. PubMed ID: 34358996
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automated detection of driver fatigue based on EEG signals using gradient boosting decision tree model.
    Hu J; Min J
    Cogn Neurodyn; 2018 Aug; 12(4):431-440. PubMed ID: 30137879
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A New Method Based on CEEMD Combined With Iterative Feature Reduction for Aided Diagnosis of Epileptic EEG.
    Zhou M; Bian K; Hu F; Lai W
    Front Bioeng Biotechnol; 2020; 8():669. PubMed ID: 32695761
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Epilepsy Seizures Prediction Based on Nonlinear Features of EEG Signal and Gradient Boosting Decision Tree.
    Xu X; Lin M; Xu T
    Int J Environ Res Public Health; 2022 Sep; 19(18):. PubMed ID: 36141613
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier.
    Al-Salman W; Li Y; Wen P
    Neurosci Res; 2021 Nov; 172():26-40. PubMed ID: 33965451
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Epileptic seizure detection in EEG signal with GModPCA and support vector machine.
    Jaiswal AK; Banka H
    Biomed Mater Eng; 2017; 28(2):141-157. PubMed ID: 28372267
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Use of radiomics based on
    Zhou Y; Ma XL; Zhang T; Wang J; Zhang T; Tian R
    Eur J Nucl Med Mol Imaging; 2021 Aug; 48(9):2904-2913. PubMed ID: 33547553
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Detecting epileptic seizure with different feature extracting strategies using robust machine learning classification techniques by applying advance parameter optimization approach.
    Hussain L
    Cogn Neurodyn; 2018 Jun; 12(3):271-294. PubMed ID: 29765477
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Epileptic seizure detection in EEG signal using machine learning techniques.
    Jaiswal AK; Banka H
    Australas Phys Eng Sci Med; 2018 Mar; 41(1):81-94. PubMed ID: 29264792
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Feature extraction and recognition of ictal EEG using EMD and SVM.
    Li S; Zhou W; Yuan Q; Geng S; Cai D
    Comput Biol Med; 2013 Aug; 43(7):807-16. PubMed ID: 23746721
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Detecting Epileptic Seizures in EEG Signals with Complementary Ensemble Empirical Mode Decomposition and Extreme Gradient Boosting.
    Wu J; Zhou T; Li T
    Entropy (Basel); 2020 Jan; 22(2):. PubMed ID: 33285915
    [TBL] [Abstract][Full Text] [Related]  

  • 20. DWT-EMD Feature Level Fusion Based Approach over Multi and Single Channel EEG Signals for Seizure Detection.
    Jana GC; Agrawal A; Pattnaik PK; Sain M
    Diagnostics (Basel); 2022 Jan; 12(2):. PubMed ID: 35204415
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.