Machine learning has shown utility in detecting patterns within large, unstructured, and
complex datasets. One of the promising applications of machine learning is in precision …

Ensemble learning is a prolific field in Machine Learning since it is based on the assumption
that combining the output of multiple models is better than using a single model, and it …

High-dimensional data analysis is a challenge for researchers and engineers in the fields of
machine learning and data mining. Feature selection provides an effective way to solve this …

Ensemble learning has been the focus of much attention, based on the assumption that
combining the output of multiple experts is better than the output of any single expert. Many …

The study of sleep stages and the associated signals have emerged as a very important
parameter to identify the neurological disorders and test of mental activities nowadays …

Automatic diagnosis of the Sleep Apnea‐Hypopnea Syndrome (SAHS) has become an
important area of research due to the growing interest in the field of sleep medicine and the …

The main objective of this work is to obtain a method that achieves the best accuracy results
with a low false positive rate in the classification of K-complexes, a kind of transient …

Highlights•A comparative study over respiratory pattern classification in the field of
SAHS.•Several missing data imputation techniques and machine learning algorithms were …

Objective To assess the validity of an automatic EEG arousal detection algorithm using large
patient samples and different heterogeneous databases. Methods Automatic scorings were …

Background Youths face significant mental health challenges exacerbated by stressful life
events, particularly in the context of the COVID-19 pandemic. Immature coping strategies …