Deep Learning (DL) has recently become a topic of study in different applications including
healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a …

Machine learning–based medical anomaly detection is an important problem that has been
extensively studied. Numerous approaches have been proposed across various medical …

The classification of electrocardiogram (ECG) signals is very important for the automatic
diagnosis of heart disease. Traditionally, it is divided into two steps, including the step of …

Artificial intelligence methods are utilized in biological signal processing to locate and
extract interesting data. The examination of ECG signal characteristics is crucial for the …

Background Market-applicable concurrent electrocardiogram (ECG) diagnosis for multiple
heart abnormalities that covers a wide range of arrhythmias, with better-than-human …

Multiple cardiovascular disease classification from Electrocardiogram (ECG) signal is
necessary for efficient and fast remedial treatment of the patient. This paper presents a …

Electrocardiogram (ECG) is the most common and low‐cost diagnostic tool used in
healthcare institutes for screening heart electrical signals. The abnormal heart signals are …

Securing personal authentication is an important study in the field of security. Particularly,
fingerprinting and face recognition have been used for personal authentication. However …

The early and accurate detection of the onset of acute myocardial infarction (AMI) is
imperative for the timely provision of medical intervention and the reduction of its mortality …

Objective: Despitethe proliferation of numerous deep learning methods proposed for generic
ECG classification and arrhythmia detection, compact systems with the real-time ability and …