[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 …
Computational diagnostic techniques for electrocardiogram signal analysis
Cardiovascular diseases (CVDs), including asymptomatic myocardial ischemia, angina,
myocardial infarction, and ischemic heart failure, are the leading cause of death globally …
myocardial infarction, and ischemic heart failure, are the leading cause of death globally …
Lungs nodule detection framework from computed tomography images using support vector machine
The emergence of cloud infrastructure has the potential to provide significant benefits in a
variety of areas in the medical imaging field. The driving force behind the extensive use of …
variety of areas in the medical imaging field. The driving force behind the extensive use of …
Convolutional neural network based automatic screening tool for cardiovascular diseases using different intervals of ECG signals
Abstract Background and Objective: Automatic screening tools can be applied to detect
cardiovascular diseases (CVDs), which are the leading cause of death worldwide. As an …
cardiovascular diseases (CVDs), which are the leading cause of death worldwide. As an …
A systematic review of time series classification techniques used in biomedical applications
Background: Digital clinical measures collected via various digital sensing technologies
such as smartphones, smartwatches, wearables, and ingestible and implantable sensors …
such as smartphones, smartwatches, wearables, and ingestible and implantable sensors …
Automating detection and localization of myocardial infarction using shallow and end-to-end deep neural networks
Myocardial infarction (MI), also known as a heart attack, is one of the common cardiac
disorders caused by prolonged myocardial ischemia. For MI patients, specifying the exact …
disorders caused by prolonged myocardial ischemia. For MI patients, specifying the exact …
A visually interpretable detection method combines 3-D ECG with a multi-VGG neural network for myocardial infarction identification
R Fang, CC Lu, CT Chuang, WH Chang - Computer Methods and Programs …, 2022 - Elsevier
Abstract Background and Objective The automatic recognition of myocardial infarction (MI)
by artificial intelligence (AI) has been an emerging topic of academic research and an …
by artificial intelligence (AI) has been an emerging topic of academic research and an …
DeepMI: Deep multi-lead ECG fusion for identifying myocardial infarction and its occurrence-time
GA Tadesse, H Javed, K Weldemariam, Y Liu… - Artificial Intelligence in …, 2021 - Elsevier
Myocardial Infarction (MI) has the highest mortality of all cardiovascular diseases (CVDs).
Detection of MI and information regarding its occurrence-time in particular, would enable …
Detection of MI and information regarding its occurrence-time in particular, would enable …
Early detection of myocardial ischemia in 12‐lead ECG using deterministic learning and ensemble learning
Q Sun, C Liang, T Chen, B Ji, R Liu, L Wang… - Computer Methods and …, 2022 - Elsevier
Background and objective: Early detection of myocardial ischemia is a necessary but difficult
problem in cardiovascular diseases. Approaches that exclusively rely on classical ST and T …
problem in cardiovascular diseases. Approaches that exclusively rely on classical ST and T …
Multilevel hybrid accurate handcrafted model for myocardial infarction classification using ECG signals
Myocardial infarction (MI) is detected using electrocardiography (ECG) signals. Machine
learning (ML) models have been used for automated MI detection on ECG signals. Deep …
learning (ML) models have been used for automated MI detection on ECG signals. Deep …