[HTML][HTML] A Fast and Cost-Effective Electronic Nose Model for Methanol Detection Using Ensemble Learning
BH Tozlu - Chemosensors, 2024 - mdpi.com
Methanol, commonly used to cut costs in the production of counterfeit alcohol, is extremely
harmful to human health, potentially leading to severe outcomes, including death. In this …
harmful to human health, potentially leading to severe outcomes, including death. In this …
[PDF][PDF] Quantifying breast cancer: radiomics, machine learning, and dimensionality reduction for enhanced image-based diagnosis
Z Ali Ansari, M Madhava Tripathi… - International Journal of …, 2024 - researchgate.net
Radiomics allows for measuring tumour heterogeneity, discovering prognostic biomarkers,
early detection and diagnosis, and combining with machine learning to improve clinical …
early detection and diagnosis, and combining with machine learning to improve clinical …
A two-stage feature redundancy minimization methodology framework for motor imagery EEG classification
H Li, Z Lu, Y Mo, B Feng, T Yu - Multimedia Tools and Applications, 2025 - Springer
The temporal-frequency-spatial features of motor imagery electroencephalogram (EEG)
signals provide comprehensive information for classification. However, these features also …
signals provide comprehensive information for classification. However, these features also …
Generative Adversarial Networks for Motor Imagery Classification using Wavelet Packet Decomposition and Complex Morlet Transform
The area of brain-computer interface research is widely spreading as it has a diverse array
of potential applications. Motor imagery classification is a boon to several people with motor …
of potential applications. Motor imagery classification is a boon to several people with motor …
[HTML][HTML] Noninvasive brain stimulation during EEG improves machine learning classification in chronic stroke
RE Suresh, MS Zobaer, MJ Triano, BF Saway… - Research …, 2024 - pmc.ncbi.nlm.nih.gov
Background: In individuals with chronic stroke and hemiparesis, noninvasive brain
stimulation (NIBS) may be used as an adjunct to therapy for improving motor recovery …
stimulation (NIBS) may be used as an adjunct to therapy for improving motor recovery …
The Application of Entropy in Motor Imagery Paradigms of Brain–Computer Interfaces
C Wu, B Yao, X Zhang, T Li, J Wang, J Pu - Brain Sciences, 2025 - mdpi.com
Background: In motor imagery brain–computer interface (MI-BCI) research,
electroencephalogram (EEG) signals are complex and nonlinear. This complexity and …
electroencephalogram (EEG) signals are complex and nonlinear. This complexity and …
Classification of Motor Imagery Tasks Using EEG Signal Analysis and Linear Discriminant Analysis
M Bafoly, R Ajoodha - … on Information and Communication Technology for …, 2024 - Springer
Abstract Brain-Computer Interfaces (BCIs) are at the forefront of technologies bridging
human cognition with external devices by interpreting brain signals. This study introduces a …
human cognition with external devices by interpreting brain signals. This study introduces a …
Kalp Yetmezliği Tanılı Hastaların Hayatta Kalma Tahmininde Topluluk Makine Öğrenme Yöntemlerinin Performans Analizi
Kalp yetmezliği önemli morbidite ve mortaliteye sahip bir kardiyovasküler hastalık olup,
dünya çapında giderek daha fazla insanı etkilemektedir. Klinik verilerle kalp yetmezliği tanılı …
dünya çapında giderek daha fazla insanı etkilemektedir. Klinik verilerle kalp yetmezliği tanılı …
[PDF][PDF] Enhancing BCI System Performance through NDD Channel Configuration
A fateh DOUDOU, A REFFAD, K MEBARKIA - ijeees.com
Motor Imagery Brain-Computer Interfaces (MI-BCIs) are artificial intelligence powered
systems designed to detect brain activity patterns linked to the mental imagination and …
systems designed to detect brain activity patterns linked to the mental imagination and …