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 *

146 related articles for article (PubMed ID: 34422035)

  • 21. Electroencephalogram variability analysis for monitoring depth of anesthesia.
    Chen YF; Fan SZ; Abbod MF; Shieh JS; Zhang M
    J Neural Eng; 2021 Nov; 18(6):. PubMed ID: 34695812
    [No Abstract]   [Full Text] [Related]  

  • 22. Quantifying the depth of anesthesia based on brain activity signal modeling.
    Huh H; Park SH; Yu JH; Hong J; Lee MJ; Cho JE; Lim CH; Lee HW; Kim JB; Yang KS; Yoon SZ
    Medicine (Baltimore); 2020 Jan; 99(5):e18441. PubMed ID: 32000357
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Sample entropy analysis of EEG signals via artificial neural networks to model patients' consciousness level based on anesthesiologists experience.
    Jiang GJ; Fan SZ; Abbod MF; Huang HH; Lan JY; Tsai FF; Chang HC; Yang YW; Chuang FL; Chiu YF; Jen KK; Wu JF; Shieh JS
    Biomed Res Int; 2015; 2015():343478. PubMed ID: 25738152
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Real-time depth of anaesthesia assessment using strong analytical signal transform technique.
    Palendeng ME; Wen P; Li Y
    Australas Phys Eng Sci Med; 2014 Dec; 37(4):723-30. PubMed ID: 25412884
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Assessment of Anesthesia Depth Using Effective Brain Connectivity Based on Transfer Entropy on EEG Signal.
    Sanjari N; Shalbaf A; Shalbaf R; Sleigh J
    Basic Clin Neurosci; 2021; 12(2):269-280. PubMed ID: 34925723
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Classifying depth of anesthesia using EEG features, a comparison.
    Esmaeili V; Shamsollahi MB; Arefian NM; Assareh A
    Annu Int Conf IEEE Eng Med Biol Soc; 2007; 2007():4106-9. PubMed ID: 18002905
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Solid waste bin level detection using gray level co-occurrence matrix feature extraction approach.
    Arebey M; Hannan MA; Begum RA; Basri H
    J Environ Manage; 2012 Aug; 104():9-18. PubMed ID: 22484654
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Emotional Stress State Detection Using Genetic Algorithm-Based Feature Selection on EEG Signals.
    Shon D; Im K; Park JH; Lim DS; Jang B; Kim JM
    Int J Environ Res Public Health; 2018 Nov; 15(11):. PubMed ID: 30400575
    [TBL] [Abstract][Full Text] [Related]  

  • 29. EEG complexity as a measure of depth of anesthesia for patients.
    Zhang XS; Roy RJ; Jensen EW
    IEEE Trans Biomed Eng; 2001 Dec; 48(12):1424-33. PubMed ID: 11759923
    [TBL] [Abstract][Full Text] [Related]  

  • 30. A Real-Time Depth of Anesthesia Monitoring System Based on Deep Neural Network With Large EDO Tolerant EEG Analog Front-End.
    Park Y; Han SH; Byun W; Kim JH; Lee HC; Kim SJ
    IEEE Trans Biomed Circuits Syst; 2020 Aug; 14(4):825-837. PubMed ID: 32746339
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Time-frequency texture descriptors of EEG signals for efficient detection of epileptic seizure.
    Şengür A; Guo Y; Akbulut Y
    Brain Inform; 2016 Jun; 3(2):101-108. PubMed ID: 27747603
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Monitoring Depth of Anesthesia Based on Hybrid Features and Recurrent Neural Network.
    Li R; Wu Q; Liu J; Wu Q; Li C; Zhao Q
    Front Neurosci; 2020; 14():26. PubMed ID: 32116494
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Distinguishing Parkinson's Disease with GLCM Features from the Hankelization of EEG Signals.
    Karakaş MF; Latifoğlu F
    Diagnostics (Basel); 2023 May; 13(10):. PubMed ID: 37238253
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Epileptic Seizure Detection Based on Time-Frequency Images of EEG Signals Using Gaussian Mixture Model and Gray Level Co-Occurrence Matrix Features.
    Li Y; Cui W; Luo M; Li K; Wang L
    Int J Neural Syst; 2018 Sep; 28(7):1850003. PubMed ID: 29607682
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Quasi-Periodicities Detection Using Phase-Rectified Signal Averaging in EEG Signals as a Depth of Anesthesia Monitor.
    Liu Q; Chen YF; Fan SZ; Abbod MF; Shieh JS
    IEEE Trans Neural Syst Rehabil Eng; 2017 Oct; 25(10):1773-1784. PubMed ID: 28391200
    [TBL] [Abstract][Full Text] [Related]  

  • 36. A cepstral analysis based method for quantifying the depth of anesthesia from human EEG.
    Kim TH; Yoon YG; Uhm J; Jeong DW; Yoon SZ; Park SH
    Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():5994-7. PubMed ID: 24111105
    [TBL] [Abstract][Full Text] [Related]  

  • 37. A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring.
    Su C; Liang Z; Li X; Li D; Li Y; Ursino M
    PLoS One; 2016; 11(10):e0164104. PubMed ID: 27723803
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Measuring the hypnotic depth of anaesthesia based on the EEG signal using combined wavelet transform, eigenvector and normalisation techniques.
    Nguyen-Ky T; Wen P; Li Y; Malan M
    Comput Biol Med; 2012 Jun; 42(6):680-91. PubMed ID: 22575174
    [TBL] [Abstract][Full Text] [Related]  

  • 39. [Monitoring the depth of anesthesia using a fuzzy neural network based on EEG].
    Li M; Ye ZQ
    Zhongguo Yi Liao Qi Xie Za Zhi; 2006 Jul; 30(4):253-5. PubMed ID: 17039930
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Auto-mutual information function of the EEG as a measure of depth of anesthesia.
    Julitta B; Vallverdu M; Melia US; Tupaika N; Jospin M; Jensen EW; Struys MM; Vereecke HE; Caminal P
    Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():2574-7. PubMed ID: 22254867
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.