Açık Akademik Arşiv Sistemi

Browsing by Author "Tuncer, Turker"

Browsing by Author "Tuncer, Turker"

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  • Automated major depressive disorder detection using melamine pattern with EEG signals 
    Aydemir, Emrah; Tuncer, Turker; Dogan, Sengul; Gururajan, Raj; Acharya, U. Rajendra (SPRINGER, 2021)
    Major depressive disorder (MDD) is one of the most common modern ailments affected huge population throughout the world. The electroencephalogram (EEG) signal is widely used to screen the MDD. The manual diagnosis of MDD ...
  • CGP17Pat: Automated Schizophrenia Detection Based on a Cyclic Group of Prime Order Patterns Using EEG Signals 
    Aydemir, Emrah; Dogan, Sengul; Baygin, Mehmet; Ooi, Chui Ping; Barua, Prabal Datta; Tuncer, Turker; Acharya, U. Rajendra (MDPI, 2022)
    Background and Purpose: Machine learning models have been used to diagnose schizophrenia. The main purpose of this research is to introduce an effective schizophrenia hand-modeled classification method. Method: A public ...
  • Hybrid Deep Feature Generation for Appropriate Face Mask Use Detection 
    Aydemir, Emrah; Yalcinkaya, Mehmet Ali; Barua, Prabal Datta; Baygin, Mehmet; Faust, Oliver; Dogan, Sengul; Chakraborty, Subrata; Tuncer, Turker; Acharya, U. Rajendra (MDPI, 2022)
    Mask usage is one of the most important precautions to limit the spread of COVID-19. Therefore, hygiene rules enforce the correct use of face coverings. Automated mask usage classification might be used to improve compliance ...
  • L-Tetrolet Pattern-Based Sleep Stage Classification Model Using Balanced EEG Datasets 
    Barua, Prabal Datta; Tuncer, Ilknur; Aydemir, Emrah; Faust, Oliver; Chakraborty, Subrata; Subbhuraam, Vinithasree; Tuncer, Turker; Dogan, Sengul; Acharya, U. Rajendra (MDPI, 2022)
    Background: Sleep stage classification is a crucial process for the diagnosis of sleep or sleep-related diseases. Currently, this process is based on manual electroencephalogram (EEG) analysis, which is resource-intensive ...
  • Mental performance classification using fused multilevel feature generation with EEG signals 
    Aydemir, Emrah; Baygin, Mehmet; Dogan, Sengul; Tuncer, Turker; Barua, Prabal Datta; Chakraborty, Subrata; Faust, Oliver; Arunkumar, N.; Kaysi, Feyzi (2022)
    Mental performance classification is a critical issue for brain-computer interfaces. Accurate and reliable classification of good or bad mental performance gives important clues for the preliminary diagnosis of some diseases ...
  • Multilevel hybrid accurate handcrafted model for myocardial infarction classification using ECG signals 
    Barua, Prabal Datta; Aydemir, Emrah; Dogan, Sengul; Kobat, Mehmet Ali; Demir, Fahrettin Burak; Baygin, Mehmet; Tuncer, Turker; Oh, Shu Lih; Tan, Ru-San; Acharya, U. Rajendra (SPRINGER HEIDELBERG, )
    Myocardial infarction (MI) is detected using electrocardiography (ECG) signals. Machine learning (ML) models have been used for automated MI detection on ECG signals. Deep learning models generally yield high classification ...
  • Novel favipiravir pattern-based learning model for automated detection of specific language impairment disorder using vowels 
    Barua, Prabal Datta; Aydemir, Emrah; Dogan, Sengul; Erten, Mehmet; Kaysi, Feyzi; Tuncer, Turker; Fujita, Hamido; Palmer, Elizabeth; Acharya, U. Rajendra (SPRINGER LONDON LTD, )
    Specific language impairment (SLI) is one of the most common diseases in children, and early diagnosis can help to obtain better timely therapy economically. It is difficult and time-consuming for clinicians to accurately ...