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 …

Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …

Computerized electrocardiogram (ECG) interpretation plays a critical role in the clinical ECG
workflow. Widely available digital ECG data and the algorithmic paradigm of deep learning …

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 …

Traffic flow forecasting is a necessary part in the intelligent transportation systems in
supporting dynamic and proactive traffic control and making traffic management plan …

Cardiovascular diseases are a leading cause of mortality globally. Electrocardiography
(ECG) still represents the benchmark approach for identifying cardiac irregularities …

The electrocardiogram (ECG) plays an imperative role in the medical field, as it records
heart signal over time and is used to discover numerous cardiovascular diseases. If a …

Noninvasive on-skin electrodes record the electrical potential changes from human skin,
which reflect body condition and are applied for healthcare, sports management, and …

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 …

Purpose In this study, we aimed to develop an automatic atrial fibrillation detection
technique for the early prediction of atrial fibrillation, that can be used with wearable devices …