Работы, цитирующие эту работу

Работ: 5

Работа: The impact of the MIT-BIH Arrhythmia Database

1. A Technique for Classifying the ECG Signal into Various Possible States of the Cardiovascular System

   Talat Magrupov, Youkubjon Talatov, Malohat Magrupova +1

   СтатьяECG Monitoring and Analysis2020Цитирований: 3

   ABIABI:AkademIndex/openalex/2020.article.000944

2. A New Wavelet-Based ECG Delineator for the Evaluation of the Ventricular Innervation

   Matteo Cesari, Jesper Mehlsen, Anne-Birgitte Mehlsen +1

   СтатьяECG Monitoring and AnalysisIEEE Journal of Translational Engineering in Health and Medicine2017Цитирований: 0

   ABIABI:AkademIndex/openalex/2017.article.000112

3. A Multi-Scale Deep Learning Framework Combining MobileViT-ECA and LSTM for Accurate ECG Analysis

   Abduljabbar S. Ba Mahel, Mehdhar S. A. M. Al-Gaashani, Reem Alkanhel +4

   СтатьяECG Monitoring and AnalysisIEEE Access2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.000386

4. Attention-enhanced bidirectional LSTM for multivariate ECG arrhythmia classification: a deep learning approach with clinical validation

   Nadira Tashtemirova

   СтатьяECG Monitoring and AnalysisJournal of Artificial Intelligence Machine Learning and Neural Network2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.019177

5. Model selection method based on the neural networks for signal processing

   Z.M. Kurdoshev, E.A. Pchelintsev

   СтатьяECG Monitoring and AnalysisDigital Signal Processing2026Цитирований: 0

   ABIABI:AkademIndex/openalex/2026.article.001172