[Retracted] Machine Learning‐Based Automated Diagnostic Systems Developed for Heart Failure Prediction Using Different Types of Data Modalities: A Systematic …
A Javeed, SU Khan, L Ali, S Ali… - … Methods in Medicine, 2022 - Wiley Online Library
One of the leading causes of deaths around the globe is heart disease. Heart is an organ
that is responsible for the supply of blood to each part of the body. Coronary artery disease …
that is responsible for the supply of blood to each part of the body. Coronary artery disease …
Classification of arrhythmia by using deep learning with 2-D ECG spectral image representation
The electrocardiogram (ECG) is one of the most extensively employed signals used in the
diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture …
diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture …
Heart disease detection using deep learning methods from imbalanced ECG samples
Heart disease (HD) is a fatal disease which takes the lives of maximum people compared to
other diseases across the world. Early and accurate detection of the disease will help to …
other diseases across the world. Early and accurate detection of the disease will help to …
An exhaustive review of machine and deep learning based diagnosis of heart diseases
In comparison to other diseases, the number of deaths on Heart Disease (HD) is the highest
across the globe. The trend of death due to HD is still rising which has become a constant …
across the globe. The trend of death due to HD is still rising which has become a constant …
Recursion enhanced random forest with an improved linear model (RERF-ILM) for heart disease detection on the internet of medical things platform
C Guo, J Zhang, Y Liu, Y Xie, Z Han, J Yu - Ieee Access, 2020 - ieeexplore.ieee.org
Nowadays, Heart disease is one of the crucial impacts of mortality in the country. In clinical
data analysis, predicting cardiovascular disease is a primary challenge. Deep learning (DL) …
data analysis, predicting cardiovascular disease is a primary challenge. Deep learning (DL) …
Improved heart disease detection from ECG signal using deep learning based ensemble model
The heart disease (HD) is very fatal in nature and comparatively takes more number of lives
across the world. To save lives from the HD, early and robust detection method is essential …
across the world. To save lives from the HD, early and robust detection method is essential …
Classification of ECG signal using FFT based improved Alexnet classifier
A Kumar M, A Chakrapani - PLOS one, 2022 - journals.plos.org
Electrocardiograms (ECG) are extensively used for the diagnosis of cardiac arrhythmias.
This paper investigates the use of machine learning classification algorithms for ECG …
This paper investigates the use of machine learning classification algorithms for ECG …
Automated classification model with OTSU and CNN method for premature ventricular contraction detection
LH Wang, LJ Ding, CX Xie, SY Jiang, IC Kuo… - IEEE …, 2021 - ieeexplore.ieee.org
Premature ventricular contraction (PVC) is one of the most common arrhythmias which can
cause palpitation, cardiac arrest, and other symptoms affecting the work and rest activities of …
cause palpitation, cardiac arrest, and other symptoms affecting the work and rest activities of …
Decision support system for predicting mortality in cardiac patients based on machine learning
Researchers have proposed several automated diagnostic systems based on machine
learning and data mining techniques to predict heart failure. However, researchers have not …
learning and data mining techniques to predict heart failure. However, researchers have not …
[HTML][HTML] Machine learning-based smart wearable system for cardiac arrest monitoring using hybrid computing
Every year, the percentage of people affected by cardiovascular diseases increases
drastically. Out of them, a heart attack is the most prominent and painful disease. According …
drastically. Out of them, a heart attack is the most prominent and painful disease. According …