[HTML][HTML] Machine learning with ensemble stacking model for automated sleep staging using dual-channel EEG signal

SK Satapathy, AK Bhoi, D Loganathan… - … Signal Processing and …, 2021 - Elsevier
Sleep staging is an important part of diagnosing the different types of sleep-related disorders
because any discrepancies in the sleep scoring process may cause serious health problems …

A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain–machine interface systems

F Tahernezhad-Javazm, V Azimirad… - Journal of neural …, 2018 - iopscience.iop.org
Objective. Considering the importance and the near-future development of noninvasive
brain–machine interface (BMI) systems, this paper presents a comprehensive theoretical …

Deep learning for early detection of pathological changes in x-ray bone microstructures: case of osteoarthritis

L Jakaite, V Schetinin, J Hladůvka, S Minaev… - Scientific Reports, 2021 - nature.com
Texture features are designed to quantitatively evaluate patterns of spatial distribution of
image pixels for purposes of image analysis and interpretation. Unexplained variations in …

Intelligent diagnosis method for rolling element bearing faults using possibility theory and neural network

H Wang, P Chen - Computers & industrial engineering, 2011 - Elsevier
This paper presents an intelligent diagnosis method for a rolling element bearing; the
method is constructed on the basis of possibility theory and a fuzzy neural network with …

Prognosis of automated sleep staging based on two-layer ensemble learning stacking model using single-channel EEG signal

SK Satapathy, D Loganathan - Soft Computing, 2021 - Springer
Sleep is important part for human health and quality of life in the daily routine basis.
However, numerous individuals face sleep problems due to rapid changes occurred in both …

Financial distress prediction in banks using Group Method of Data Handling neural network, counter propagation neural network and fuzzy ARTMAP

P Ravisankar, V Ravi - Knowledge-based systems, 2010 - Elsevier
This paper presents three hitherto unused neural network architectures for bankruptcy
prediction in banks. These networks are Group Method of Data Handling (GMDH), Counter …

Human facial expression recognition with convolution neural networks

N Christou, N Kanojiya - Third International Congress on Information and …, 2019 - Springer
Facial expression recognition (FER) is an active area in machine learning research, where
human–machine interaction is prevalent for developing applications such as health care …

Feature extraction with GMDH-type neural networks for EEG-based person identification

V Schetinin, L Jakaite, N Nyah… - … Journal of Neural …, 2018 - World Scientific
The brain activity observed on EEG electrodes is influenced by volume conduction and
functional connectivity of a person performing a task. When the task is a biometric test the …

Bayesian averaging over decision tree models: an application for estimating uncertainty in trauma severity scoring

V Schetinin, L Jakaite, W Krzanowski - International journal of medical …, 2018 - Elsevier
Introduction For making reliable decisions, practitioners need to estimate uncertainties that
exist in data and decision models. In this paper we analyse uncertainties of predicting …

[PDF][PDF] Fault diagnosis of centrifugal pump using symptom parameters in frequency domain

HQ Wang, P Chen - Agricultural Engineering International: CIGR …, 2007 - cigrjournal.org
This paper presents a fault diagnosis method for a centrifugal pump system with frequency-
domain symptom parameters by using the wavelet transform, rough sets and a fuzzy neural …