Abstract Background and Objective In recent years, stress and mental health have been
considered as important worldwide concerns. Stress detection using physiological signals …

This paper examines the use of machine learning and deep learning algorithms in the
aviation industry, with a specific emphasis on aircraft diagnosis/prognosis, predictive …

The rapid development of information technology has led to the development of medical
informatization in the direction of intelligence. Medical health big data provides a basic data …

Feature selection is a significant task in data mining and machine learning applications
which eliminates irrelevant and redundant features and improves learning performance. In …

The use of a low-cost five-band multispectral camera (RedEdge, MicaSense, USA) and a
low-altitude airborne platform is investigated for the detection of plant stress caused by …

We developed a novel computer-aided diagnosis (CAD) system that uses feature-ranking
and a genetic algorithm to analyze structural magnetic resonance imaging data; using this …

Over many decades, research is being attempted for the detection of epileptic seizure to
support for automatic diagnosis system to help clinicians from burdensome work. In this …

Computer-aided heartbeat classification has a significant role in the diagnosis of cardiac
dysfunction. Electrocardiogram (ECG) provides vital information about the heartbeats. In this …

Emotion recognition system from speech signal is a widely researched topic in the design of
the Human–Computer Interface (HCI) models, since it provides insights into the mental …

Music has the ability to evoke different emotions in people, which is reflected in their
physiological signals. Advances in affective computing have introduced computational …