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 *

129 related articles for article (PubMed ID: 38187293)

  • 1. Diagnosis of atrial fibrillation based on AI-detected anomalies of ECG segments.
    Choi S; Choi K; Yun HK; Kim SH; Choi HH; Park YS; Joo S
    Heliyon; 2024 Jan; 10(1):e23597. PubMed ID: 38187293
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Semi-supervised Algorithm for Atrial Fibrillation Attack Prediction Using Convolution Auto-encoder of Time Series Signal.
    Jiang Y; Zheng P; Lai D
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38082861
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Semi-Supervised Learning for Automatic Atrial Fibrillation Detection in 24-Hour Holter Monitoring.
    Zhang P; Chen Y; Lin F; Wu S; Yang X; Li Q
    IEEE J Biomed Health Inform; 2022 Aug; 26(8):3791-3801. PubMed ID: 35536820
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Short-term atrial fibrillation detection using electrocardiograms: A comparison of machine learning approaches.
    Jahan MS; Mansourvar M; Puthusserypady S; Wiil UK; Peimankar A
    Int J Med Inform; 2022 Jul; 163():104790. PubMed ID: 35552189
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Over-fitting suppression training strategies for deep learning-based atrial fibrillation detection.
    Zhang X; Li J; Cai Z; Zhang L; Chen Z; Liu C
    Med Biol Eng Comput; 2021 Jan; 59(1):165-173. PubMed ID: 33387183
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deepaware: A hybrid deep learning and context-aware heuristics-based model for atrial fibrillation detection.
    Kumar D; Peimankar A; Sharma K; Domínguez H; Puthusserypady S; Bardram JE
    Comput Methods Programs Biomed; 2022 Jun; 221():106899. PubMed ID: 35640394
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Short Single-Lead ECG Signal Delineation-Based Deep Learning: Implementation in Automatic Atrial Fibrillation Identification.
    Tutuko B; Rachmatullah MN; Darmawahyuni A; Nurmaini S; Tondas AE; Passarella R; Partan RU; Rifai A; Sapitri AI; Firdaus F
    Sensors (Basel); 2022 Mar; 22(6):. PubMed ID: 35336500
    [TBL] [Abstract][Full Text] [Related]  

  • 8. An accurate and efficient method to train classifiers for atrial fibrillation detection in ECGs: Learning by asking better questions.
    Wesselius FJ; van Schie MS; de Groot NMS; Hendriks RC
    Comput Biol Med; 2022 Apr; 143():105331. PubMed ID: 35231835
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Few-shot transfer learning for personalized atrial fibrillation detection using patient-based siamese network with single-lead ECG records.
    Ng Y; Liao MT; Chen TL; Lee CK; Chou CY; Wang W
    Artif Intell Med; 2023 Oct; 144():102644. PubMed ID: 37783539
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A morphology based deep learning model for atrial fibrillation detection using single cycle electrocardiographic samples.
    Baalman SWE; Schroevers FE; Oakley AJ; Brouwer TF; van der Stuijt W; Bleijendaal H; Ramos LA; Lopes RR; Marquering HA; Knops RE; de Groot JR
    Int J Cardiol; 2020 Oct; 316():130-136. PubMed ID: 32315684
    [TBL] [Abstract][Full Text] [Related]  

  • 11. SEResUTer: a deep learning approach for accurate ECG signal delineation and atrial fibrillation detection.
    Li X; Cai W; Xu B; Jiang Y; Qi M; Wang M
    Physiol Meas; 2023 Dec; 44(12):. PubMed ID: 37827168
    [No Abstract]   [Full Text] [Related]  

  • 12. Automated Atrial Fibrillation Diagnosis by Echocardiography without ECG: Accuracy and Applications of a New Deep Learning Approach.
    Lu N; Vaseli H; Mahdavi M; Taheri Dezaki F; Luong C; Yeung D; Gin K; Tsang M; Nair P; Jue J; Barnes M; Behnami D; Abolmaesumi P; Tsang TSM
    Diseases; 2024 Feb; 12(2):. PubMed ID: 38391782
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Automated diagnosis of atrial fibrillation using ECG component-aware transformer.
    Yang MU; Lee DI; Park S
    Comput Biol Med; 2022 Nov; 150():106115. PubMed ID: 36179512
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Global hybrid multi-scale convolutional network for accurate and robust detection of atrial fibrillation using single-lead ECG recordings.
    Zhang P; Ma C; Sun Y; Fan G; Song F; Feng Y; Zhang G
    Comput Biol Med; 2021 Dec; 139():104880. PubMed ID: 34700255
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Extracting deep features from short ECG signals for early atrial fibrillation detection.
    Wu X; Zheng Y; Chu CH; He Z
    Artif Intell Med; 2020 Sep; 109():101896. PubMed ID: 34756213
    [TBL] [Abstract][Full Text] [Related]  

  • 16. LTH-ECG: Lottery Ticket Hypothesis-based Deep Learning Model Compression for Atrial Fibrillation Detection from Single Lead ECG On Wearable and Implantable Devices.
    Sahu I; Ukil A; Khandelwal S; Pal A
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():1655-1658. PubMed ID: 36085683
    [TBL] [Abstract][Full Text] [Related]  

  • 17. AFCNNet: Automated detection of AF using chirplet transform and deep convolutional bidirectional long short term memory network with ECG signals.
    Radhakrishnan T; Karhade J; Ghosh SK; Muduli PR; Tripathy RK; Acharya UR
    Comput Biol Med; 2021 Oct; 137():104783. PubMed ID: 34481184
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Integrating Clinical, Genetic, and Electrocardiogram-Based Artificial Intelligence to Estimate Risk of Incident Atrial Fibrillation.
    Kany S; Rämö JT; Friedman SF; Weng LC; Roselli C; Kim MS; Fahed AC; Lubitz SA; Maddah M; Ellinor PT; Khurshid S
    medRxiv; 2024 Aug; ():. PubMed ID: 39185529
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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; 18(21):. PubMed ID: 34769819
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Anomaly Detection for Sensor Signals Utilizing Deep Learning Autoencoder-Based Neural Networks.
    Esmaeili F; Cassie E; Nguyen HPT; Plank NOV; Unsworth CP; Wang A
    Bioengineering (Basel); 2023 Mar; 10(4):. PubMed ID: 37106591
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.