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 *

226 related articles for article (PubMed ID: 28316639)

  • 1. Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine.
    Chen L; Hao Y
    Comput Math Methods Med; 2017; 2017():7949507. PubMed ID: 28316639
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Relevant Features Selection for Automatic Prediction of Preterm Deliveries from Pregnancy ElectroHysterograhic (EHG) records.
    Sadi-Ahmed N; Kacha B; Taleb H; Kedir-Talha M
    J Med Syst; 2017 Nov; 41(12):204. PubMed ID: 29128973
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A New Efficient Algorithm for Prediction of Preterm Labor.
    Shahbakhti M; Beiramvand M; Bavi MR; Mohammadi Far S
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():4669-4672. PubMed ID: 31946904
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of Preterm Delivery from Unbalanced EHG Database.
    Mohammadi Far S; Beiramvand M; Shahbakhti M; Augustyniak P
    Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214412
    [TBL] [Abstract][Full Text] [Related]  

  • 5. [Prognostic value of chosen parameters of mechanical and bioelectrical uterine activity in prediction of threatening preterm labour].
    Zietek J; Sikora J; Horoba K; Matonia A; Jezewski J; Magnucki J; Kobielska L
    Ginekol Pol; 2009 Mar; 80(3):193-200. PubMed ID: 19382611
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Prediction of Preterm Labor from the Electrohysterogram Signals Based on Different Gestational Weeks.
    Mohammadi Far S; Beiramvand M; Shahbakhti M; Augustyniak P
    Sensors (Basel); 2023 Jun; 23(13):. PubMed ID: 37447815
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automated detection of premature delivery using empirical mode and wavelet packet decomposition techniques with uterine electromyogram signals.
    Acharya UR; Sudarshan VK; Rong SQ; Tan Z; Lim CM; Koh JE; Nayak S; Bhandary SV
    Comput Biol Med; 2017 Jun; 85():33-42. PubMed ID: 28433870
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Automatic Multi-Level In-Exhale Segmentation and Enhanced Generalized S-Transform for wheezing detection.
    Chen H; Yuan X; Li J; Pei Z; Zheng X
    Comput Methods Programs Biomed; 2019 Sep; 178():163-173. PubMed ID: 31416545
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Performance comparison of coupling-evaluation methods in discriminating between pregnancy and labor EHG signals.
    Diab A; Boudaoud S; Karlsson B; Marque C
    Comput Biol Med; 2021 May; 132():104308. PubMed ID: 33711558
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A multichannel time-frequency and multi-wavelet toolbox for uterine electromyography processing and visualisation.
    Batista AG; Najdi S; Godinho DM; Martins C; Serrano FC; Ortigueira MD; Rato RT
    Comput Biol Med; 2016 Sep; 76():178-91. PubMed ID: 27474810
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Combination of canonical correlation analysis and empirical mode decomposition applied to denoising the labor electrohysterogram.
    Hassan M; Boudaoud S; Terrien J; Karlsson B; Marque C
    IEEE Trans Biomed Eng; 2011 Sep; 58(9):2441-7. PubMed ID: 21558055
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Network Theory Based EHG Signal Analysis and its Application in Preterm Prediction.
    Xu J; Wang M; Zhang J; Chen Z; Huang W; Shen G; Zhang M
    IEEE J Biomed Health Inform; 2022 Jul; 26(7):2876-2887. PubMed ID: 34986107
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Uterine electromyogram database and processing function interface: An open standard analysis platform for electrohysterogram signals.
    Terrien J; Marque C; Gondry J; Steingrimsdottir T; Karlsson B
    Comput Biol Med; 2010 Feb; 40(2):223-30. PubMed ID: 20056198
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep neural network for semi-automatic classification of term and preterm uterine recordings.
    Chen L; Xu H
    Artif Intell Med; 2020 May; 105():101861. PubMed ID: 32505424
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Fault Diagnosis for Analog Circuits by Using EEMD, Relative Entropy, and ELM.
    Xiong J; Tian S; Yang C
    Comput Intell Neurosci; 2016; 2016():7657054. PubMed ID: 27698663
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Novel Characteristic Frequency Bands Extraction Method for Automatic Bearing Fault Diagnosis Based on Hilbert Huang Transform.
    Yu X; Ding E; Chen C; Liu X; Li L
    Sensors (Basel); 2015 Nov; 15(11):27869-93. PubMed ID: 26540059
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A validation of electrohysterography for uterine activity monitoring during labour.
    Jacod BC; Graatsma EM; Van Hagen E; Visser GH
    J Matern Fetal Neonatal Med; 2010 Jan; 23(1):17-22. PubMed ID: 19672790
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Preterm-term birth classification using EMD-based time-domain features of single-channel electrohysterogram data.
    Janjarasjitt S
    Phys Eng Sci Med; 2021 Dec; 44(4):1151-1159. PubMed ID: 34463948
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Accuracy of frequency-related parameters of the electrohysterogram for predicting preterm delivery: a review of the literature.
    Vinken MP; Rabotti C; Mischi M; Oei SG
    Obstet Gynecol Surv; 2009 Aug; 64(8):529-41. PubMed ID: 19624864
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Realistic preterm prediction based on optimized synthetic sampling of EHG signal.
    Xu J; Chen Z; Zhang J; Lu Y; Yang X; Pumir A
    Comput Biol Med; 2021 Sep; 136():104644. PubMed ID: 34271407
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.