Intelligent deep model based on convolutional neural network's and multi-layer perceptron to classify cardiac abnormality in diabetic patients

M Saraswat, AK Wadhwani, S Wadhwani - Physical and Engineering …, 2024 - Springer
The ECG is a crucial tool in the medical field for recording the heartbeat signal over time,
aiding in the identification of various cardiac diseases. Commonly, the interpretation of …

[HTML][HTML] Automated detection of abnormalities in ECG signals using deep neural network

SG Begum, E Priyadarshi, S Pratap… - Biomedical Engineering …, 2023 - Elsevier
The electrocardiogram (ECG) is a diagnostic procedure that uses a skin electrode to record
the heart's electrical activity. Heart diseases are the leading cause of mortality globally, and …

Heart disease detection through deep learning model RNN

DD Kamble, PH Kale, SP Nitture, KV Waghmare… - … Applications, Volume 2 …, 2022 - Springer
Heart diseases are a problematic occurrence that has been getting more and more frequent
in recent years. This might be due to the increasing elderly population across the world …

[PDF][PDF] Detection of Cardiovascular Diseases Using Machine Learning and Deep Learning

P Rai, SK Fernandes, T Choedon, TT Bhutia - 2023 - easychair.org
Cardiovascular diseases also known as heart diseases are the leading cause of death on a
global scale. Early detection of cardiac abnormalities can save many lives and even assist …

Detection of arrhythmia and congestive heart failure through classification of ECG signals using deep learning neural network

S Krishnakumar, M Yasodha… - … on advancements in …, 2021 - ieeexplore.ieee.org
Globally, cardiovascular illnesses are the major cause of death. By detecting the electrical
activity of the heart as it contracts, electrocardiogram (ECG) data can be used to detect heart …

Classification of ECG signals using deep neural networks

N Mohamed, C Lakhmissi, H Nadji - The Journal of Engineering …, 2023 - periodicos.ufv.br
The electrocardiogram (ECG) is an essential tool in the field of cardiology, as it enables the
electrical activity of the heart to be measured. It involves placing electrodes on the patient's …

Hybrid CNN-LSTM deep learning model and ensemble technique for automatic detection of myocardial infarction using big ECG data

HM Rai, K Chatterjee - Applied Intelligence, 2022 - Springer
Automatic and accurate prognosis of myocardial infarction (MI) using electrocardiogram
(ECG) signals is a challenging task for the diagnosis and treatment of heart diseases. MI is …

[PDF][PDF] Design and Comparison of Deep Learning Model for ECG Classification using PTB-XL Dataset

MN Bhanjaa, P Khampariya - 2023 - researchgate.net
The classification of distinct types of electrocardiogram (ECG) signals, such as Normal, ST/T
Change, Hypertrophy, Conduction Disturbance, and Myocardial Infarction using deep …

[PDF][PDF] Automated Detection of Cardiovascular Diseases using Deep Learning and Electrocardiogram (ECG) Images: A Convolutional Neural Network Approach

MF El-Habibi - complexity, 2023 - researchgate.net
Cardiovascular diseases (CVDs) pose a significant threat to human health worldwide due to
their severity and high prevalence. They are responsible for a substantial number of deaths …

[PDF][PDF] Classification of Diabetes and Cardiac Arrhythmia using Deep Learning

M Dutt - 2018 - uia.brage.unit.no
Deep Learning (DL) is a research area that has ourished signi cantly in the recent years and
has shown remarkable potential for arti cial intelligence in the eld of medical applications …