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.
2. A Deep Learning Method to Detect Atrial Fibrillation Based on Continuous Wavelet Transform. Wu Z, Feng X, Yang C. Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():1908-1912. PubMed ID: 31946271 [Abstract] [Full Text] [Related]
4. A Parallel Cross Convolutional Recurrent Neural Network for Automatic Imbalanced ECG Arrhythmia Detection with Continuous Wavelet Transform. Toma TI, Choi S. Sensors (Basel); 2022 Sep 28; 22(19):. PubMed ID: 36236496 [Abstract] [Full Text] [Related]
5. TP-CNN: A Detection Method for atrial fibrillation based on transposed projection signals with compressed sensed ECG. Zhang H, Dong Z, Sun M, Gu H, Wang Z. Comput Methods Programs Biomed; 2021 Oct 28; 210():106358. PubMed ID: 34478912 [Abstract] [Full Text] [Related]
7. Transfer Learning for Detection of Atrial Fibrillation in Deterministic Compressive Sensed ECG. Abdelazez M, Rajan S, Chan ADC. Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul 28; 2020():5398-5401. PubMed ID: 33019201 [Abstract] [Full Text] [Related]
9. Automatic Prediction of Atrial Fibrillation Based on Convolutional Neural Network Using a Short-term Normal Electrocardiogram Signal. Erdenebayar U, Kim H, Park JU, Kang D, Lee KJ. J Korean Med Sci; 2019 Feb 25; 34(7):e64. PubMed ID: 30804732 [Abstract] [Full Text] [Related]
10. Detection of shockable ventricular cardiac arrhythmias from ECG signals using FFREWT filter-bank and deep convolutional neural network. Panda R, Jain S, Tripathy RK, Acharya UR. Comput Biol Med; 2020 Sep 25; 124():103939. PubMed ID: 32750507 [Abstract] [Full Text] [Related]
12. Review of Deep Learning-Based Atrial Fibrillation Detection Studies. Murat F, Sadak F, Yildirim O, Talo M, Murat E, Karabatak M, Demir Y, Tan RS, Acharya UR. Int J Environ Res Public Health; 2021 Oct 28; 18(21):. PubMed ID: 34769819 [Abstract] [Full Text] [Related]
13. Automatic Detection of Short-Term Atrial Fibrillation Segments Based on Frequency Slice Wavelet Transform and Machine Learning Techniques. Yue Y, Chen C, Liu P, Xing Y, Zhou X. Sensors (Basel); 2021 Aug 05; 21(16):. PubMed ID: 34450743 [Abstract] [Full Text] [Related]
16. Atrial Fibrillation Detection in Short Single Lead ECG Recordings Using Wavelet Transform and Artificial Neural Networks. Hernandez F, Mendez D, Amado L, Altuve M. Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul 05; 2018():5982-5985. PubMed ID: 30441699 [Abstract] [Full Text] [Related]
17. A Q-transform-based deep learning model for the classification of atrial fibrillation types. Dhananjay B, Kumar RP, Neelapu BC, Pal K, Sivaraman J. Phys Eng Sci Med; 2024 Jun 05; 47(2):621-631. PubMed ID: 38353927 [Abstract] [Full Text] [Related]
18. Atrial Fibrillation Classification with Smart Wearables Using Short-Term Heart Rate Variability and Deep Convolutional Neural Networks. Ramesh J, Solatidehkordi Z, Aburukba R, Sagahyroon A. Sensors (Basel); 2021 Oct 30; 21(21):. PubMed ID: 34770543 [Abstract] [Full Text] [Related]
19. SS-SWT and SI-CNN: An Atrial Fibrillation Detection Framework for Time-Frequency ECG Signal. Zhang H, He R, Dai H, Xu M, Wang Z. J Healthc Eng; 2020 Oct 30; 2020():7526825. PubMed ID: 32509259 [Abstract] [Full Text] [Related]