QuadTPat: Quadruple Transition Pattern-based explainable feature engineering model for stress detection using EEG signals

VY Cambay, I Tasci, G Tasci, R Hajiyeva, S Dogan… - Scientific Reports, 2024‏ - nature.com
The most cost-effective data collection method is electroencephalography (EEG), which
obtains meaningful information about the brain. Therefore, EEG signal processing is crucial …

TATPat based explainable EEG model for neonatal seizure detection

T Tuncer, S Dogan, I Tasci, B Tasci, R Hajiyeva - Scientific Reports, 2024‏ - nature.com
The most cost-effective data collection method is electroencephalography (EEG) to obtain
meaningful information about the brain. Therefore, EEG signal processing is very important …

[HTML][HTML] Zipper Pattern: An Investigation into Psychotic Criminal Detection Using EEG Signals

G Tasci, PD Barua, D Tanko, T Keles, S Tas, I Sercek… - Diagnostics, 2025‏ - mdpi.com
Background: Electroencephalography (EEG) signal-based machine learning models are
among the most cost-effective methods for information retrieval. In this context, we aimed to …

[HTML][HTML] CubicPat: Investigations on the Mental Performance and Stress Detection Using EEG Signals

U Ince, Y Talu, A Duz, S Tas, D Tanko, I Tasci, S Dogan… - Diagnostics, 2025‏ - mdpi.com
Background\Objectives: Solving the secrets of the brain is a significant challenge for
researchers. This work aims to contribute to this area by presenting a new explainable …

[HTML][HTML] ChMinMaxPat: Investigations on Violence and Stress Detection Using EEG Signals

O Bektas, S Kirik, I Tasci, R Hajiyeva, E Aydemir… - Diagnostics, 2024‏ - mdpi.com
Background and Objectives: Electroencephalography (EEG) signals, often termed the letters
of the brain, are one of the most cost-effective methods for gathering valuable information …

DoubleSENeXt: Investigations on Enchondroma Detection

EY Uslu, M Yildirim, R Hajiyeva, S Dogan… - Traitement du …, 2024‏ - search.proquest.com
There are various deep learning models used to solve computer vision problems, with
convolutional neural networks (CNNs) and transformers being commonly employed …