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.
157 related articles for article (PubMed ID: 31687121)
1. Intelligent Analysis of Premature Ventricular Contraction Based on Features and Random Forest. Xie T; Li R; Shen S; Zhang X; Zhou B; Wang Z J Healthc Eng; 2019; 2019():5787582. PubMed ID: 31687121 [TBL] [Abstract][Full Text] [Related]
2. PVC arrhythmia classification based on fractional order system modeling. Assadi I; Charef A; Bensouici T Biomed Tech (Berl); 2021 Aug; 66(4):363-373. PubMed ID: 33606930 [TBL] [Abstract][Full Text] [Related]
3. PVC discrimination using the QRS power spectrum and self-organizing maps. Talbi ML; Charef A Comput Methods Programs Biomed; 2009 Jun; 94(3):223-31. PubMed ID: 19215994 [TBL] [Abstract][Full Text] [Related]
5. Bayesian Classification Models for Premature Ventricular Contraction Detection on ECG Traces. Casas MM; Avitia RL; Gonzalez-Navarro FF; Cardenas-Haro JA; Reyna MA J Healthc Eng; 2018; 2018():2694768. PubMed ID: 29861881 [TBL] [Abstract][Full Text] [Related]
6. Localization of origins of premature ventricular contraction in the whole ventricle based on machine learning and automatic beat recognition from 12-lead ECG. He K; Nie Z; Zhong G; Yang C; Sun J Physiol Meas; 2020 Jun; 41(5):055007. PubMed ID: 32252035 [TBL] [Abstract][Full Text] [Related]
7. Automated detection of premature ventricular contraction in ECG signals using enhanced template matching algorithm. Malek AS; Elnahrawy A; Anwar H; Naeem M Biomed Phys Eng Express; 2020 Jan; 6(1):015024. PubMed ID: 33438612 [TBL] [Abstract][Full Text] [Related]
8. Automatic diagnosis of premature ventricular contraction based on Lyapunov exponents and LVQ neural network. Liu X; Du H; Wang G; Zhou S; Zhang H Comput Methods Programs Biomed; 2015 Oct; 122(1):47-55. PubMed ID: 26198132 [TBL] [Abstract][Full Text] [Related]
9. Classification of QRS complexes to detect Premature Ventricular Contraction using machine learning techniques. De Marco F; Ferrucci F; Risi M; Tortora G PLoS One; 2022; 17(8):e0268555. PubMed ID: 35980965 [TBL] [Abstract][Full Text] [Related]
10. PVC Detection Using a Convolutional Autoencoder and Random Forest Classifier. Gordon M; Williams C Pac Symp Biocomput; 2019; 24():42-53. PubMed ID: 30864309 [TBL] [Abstract][Full Text] [Related]
11. A High Precision Real-time Premature Ventricular Contraction Assessment Method based on the Complex Feature Set. Wang H; Shi H; Chen X; Zhao L; Huang Y; Liu C J Med Syst; 2019 Nov; 44(1):3. PubMed ID: 31758339 [TBL] [Abstract][Full Text] [Related]
12. Automated detection of premature ventricular contraction based on the improved gated recurrent unit network. Wang J Comput Methods Programs Biomed; 2021 Sep; 208():106284. PubMed ID: 34304005 [TBL] [Abstract][Full Text] [Related]
13. Detection of Premature Ventricular Complexes using Semisupervised Autoencoders and Random Forests. Kalidas V; Tamil LS Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():337-340. PubMed ID: 33017997 [TBL] [Abstract][Full Text] [Related]
15. Finding features for real-time premature ventricular contraction detection using a fuzzy neural network system. Lim JS IEEE Trans Neural Netw; 2009 Mar; 20(3):522-7. PubMed ID: 19179246 [TBL] [Abstract][Full Text] [Related]
16. Detection of premature ventricular contractions using the RR-interval signal: a simple algorithm for mobile devices. Cuesta P; Lado MJ; Vila XA; Alonso R Technol Health Care; 2014; 22(4):651-6. PubMed ID: 24898863 [TBL] [Abstract][Full Text] [Related]
17. A novel method of diagnosing premature ventricular contraction based on sparse auto-encoder and softmax regression. Yang J; Bai Y; Li G; Liu M; Liu X Biomed Mater Eng; 2015; 26 Suppl 1():S1549-58. PubMed ID: 26405919 [TBL] [Abstract][Full Text] [Related]
18. Classification of premature ventricular complexes using filter bank features, induction of decision trees and a fuzzy rule-based system. Wieben O; Afonso VX; Tompkins WJ Med Biol Eng Comput; 1999 Sep; 37(5):560-5. PubMed ID: 10723892 [TBL] [Abstract][Full Text] [Related]
19. Ranking of pattern recognition parameters for premature ventricular contractions classification by neural networks. Christov I; Bortolan G Physiol Meas; 2004 Oct; 25(5):1281-90. PubMed ID: 15535192 [TBL] [Abstract][Full Text] [Related]
20. [Detection of premature ventricular contraction and atrial premature contraction based on mode entropy]. Wu J; Wang J Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2010 Jun; 27(3):516-8. PubMed ID: 20649009 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]