Crccn-net: Automated framework for classification of colorectal tissue using histopathological images

A Kumar, A Vishwakarma, V Bajaj - Biomedical Signal Processing and …, 2023 - Elsevier
Colorectal cancer has a high mortality rate that continuously affects human life globally.
Early detection of it extends human life and helps in preventing disease. Histopathological …

Improved multi-layer binary firefly algorithm for optimizing feature selection and classification of microarray data

W Xie, L Wang, K Yu, T Shi, W Li - Biomedical Signal Processing and …, 2023 - Elsevier
Gene microarray technology can detect many gene expressions simultaneously, which is
essential for disease diagnosis. However, microarray data are usually characterized by …

Variational phase-amplitude coupling characterizes signatures of anterior cortex under emotional processing

C Zhang, CH Yeh, W Shi - IEEE Journal of Biomedical and …, 2023 - ieeexplore.ieee.org
Emotion, an essential aspect in inferring human psychological states, is featured by
entangled oscillators operating at multiple frequencies and montages. However, the …

Automated newborn cry diagnostic system using machine learning approach

FS Matikolaie, Y Kheddache, C Tadj - Biomedical Signal Processing and …, 2022 - Elsevier
Researchers have found that crying is an acoustic symptom among unhealthy newborns.
This study aims to develop a non-invasive newborn cry diagnostic system (NCDS) using …

[HTML][HTML] A novel deep learning model to detect COVID-19 based on wavelet features extracted from Mel-scale spectrogram of patients' cough and breathing sounds

M Aly, NS Alotaibi - Informatics in Medicine Unlocked, 2022 - Elsevier
The goal of this paper is to classify the various cough and breath sounds of COVID-19
artefacts in the signals from dynamic real-life environments. The main reason for choosing …

Attentional gated Res2Net for multivariate time series classification

C Yang, X Wang, L Yao, G Long, J Jiang… - Neural Processing Letters, 2023 - Springer
Multivariate time series classification is a critical problem in data mining with broad
applications. It requires harnessing the inter-relationship of multiple variables and various …

Clustering-fusion feature selection method in identifying major depressive disorder based on resting state EEG signals

S Sun, H Chen, G Luo, C Yan, Q Dong… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Depression is a heterogeneous syndrome with certain individual differences among
subjects. Exploring a feature selection method that can effectively mine the commonness …

Artificial neural network-based optimization of operating parameters for minimum quantity lubrication-assisted burnishing process in terms of surface characteristics

TT Nguyen, TA Nguyen, QH Trinh, XB Le… - Neural Computing and …, 2022 - Springer
Roller burnishing is an alternative approach to enhance surface properties under plastic
deformation and most investigations focused on optimizing process parameters. However …

Investigation of global brain dynamics depending on emotion regulation strategies indicated by graph theoretical brain network measures at system level

S Aydın - Cognitive Neurodynamics, 2023 - Springer
In the present study, new findings reveal the close association between graph theoretic
global brain connectivity measures and cognitive abilities the ability to manage and regulate …

How do sEMG segmentation parameters influence pattern recognition process? An approach based on wearable sEMG sensor

JJAM Junior, CE Pontim, TS Dias… - … Signal Processing and …, 2023 - Elsevier
Processing surface electromyography (sEMG) data in real-time to control robotic devices in
applications involving upper-limb prostheses is challenging, especially when the problem …