SER inspired deep learning approach to detect cardiac arrhythmias in electrocardiogram signals using Temporal Convolutional Network and graph neural network

<p dir="ltr">Electrocardiogram (ECG) signals play a critical role in diagnosing cardiovascular diseases (CVDs), yet automated ECG classification remains challenging due to inter-patient variability, signal noise, and heart rhythm complexity. To address these challenges, we propose a...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Samin Yaser (22803530) (author)
مؤلفون آخرون:	Muhammad E.H. Chowdhury (17151154) (author), Rusab Sarmun (17632269) (author)
منشور في:	2025
الموضوعات:	Biomedical and clinical sciences Cardiovascular medicine and haematology Engineering Biomedical engineering Health sciences Health services and systems Information and computing sciences Artificial intelligence Machine learning Cardiac arrhythmia Deep learning Residual Temporal Convolutional Network Feature map Graph neural network Signal processing Electrocardiogram (ECG) Classification model
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

كن أول من يترك تعليقا!

SER inspired deep learning approach to detect cardiac arrhythmias in electrocardiogram signals using Temporal Convolutional Network and graph neural network

مواد مشابهة