In the era of Internet-of-things, many things can stay connected; however, biological
systems, including those necessary for human health, remain unable to stay connected to …

Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …

Mechanical system usually operates in harsh environments, and the monitored vibration
signal faces substantial noise interference, which brings great challenges to the robust fault …

Cardiovascular disease is a major global public health problem, and intelligent diagnostic
approaches play an increasingly important role in the analysis of electrocardiograms …

Early detection is critical to achieving improved treatment outcomes for child patients with
congenital heart diseases (CHDs). Therefore, developing effective CHD detection …

Deep learning (DL) has been introduced in automatic heart-abnormality classification using
ECG signals, while its application in practical medical procedures is limited. A systematic …

Blood circulation depends critically on electrical activation, where any disturbance in the
orderly pattern of the heart's propagating wave of excitation can lead to arrhythmias …

Artificial intelligence (AI) is an integral part of clinical decision support systems (CDSS),
offering methods to approximate human reasoning and computationally infer decisions …

Background Cotton diceases seriously affect the yield and quality of cotton. The type of pest
or disease suffered by cotton can be determined by the disease spots on the cotton leaves …

Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …