Impact of eeg parameters detecting dementia diseases: A systematic review
Dementia diseases are increasing rapidly, according to the World Health Organization
(WHO), becoming an alarming problem for the health sector. The electroencephalogram …
(WHO), becoming an alarming problem for the health sector. The electroencephalogram …
A systematic review and methodological analysis of EEG-based biomarkers of Alzheimer's disease
Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders in the
world. Although there is no known cure for it at the present, preventive drug trials and …
world. Although there is no known cure for it at the present, preventive drug trials and …
Convolutional neural network for multi-class classification of diabetic eye disease
Prompt examination increases the chances of effective treatment of Diabetic Eye Disease
(DED) and reduces the likelihood of permanent deterioration of vision. A key tool commonly …
(DED) and reduces the likelihood of permanent deterioration of vision. A key tool commonly …
A long short-term memory based framework for early detection of mild cognitive impairment from EEG signals
Mild cognitive impairment (MCI) is an irreparable progressive neuro-degenerative disorder,
which seems to be a precursor to Alzheimer's disease (AD) that may lead to dementia in …
which seems to be a precursor to Alzheimer's disease (AD) that may lead to dementia in …
Brain functional networks based on resting-state EEG data for major depressive disorder analysis and classification
B Zhang, G Yan, Z Yang, Y Su… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
If the brain is regarded as a system, it will be one of the most complex systems in the
universe. Traditional analysis and classification methods of major depressive disorder …
universe. Traditional analysis and classification methods of major depressive disorder …
Depression recognition based on the reconstruction of phase space of EEG signals and geometrical features
Depression is a mental disorder that continues to make life difficult or impossible for a
depressed person and, if left untreated, can lead to dangerous activities such as self-harm …
depressed person and, if left untreated, can lead to dangerous activities such as self-harm …
A deep learning based framework for diagnosis of mild cognitive impairment
Detecting mild cognitive impairment (MCI) from electroencephalography (EEG) data is a
challenging problem as existing methods rely on machine learning based shallow …
challenging problem as existing methods rely on machine learning based shallow …
Primate brain pattern-based automated Alzheimer's disease detection model using EEG signals
Electroencephalography (EEG) may detect early changes in Alzheimer's disease (AD), a
debilitating progressive neurodegenerative disease. We have developed an automated AD …
debilitating progressive neurodegenerative disease. We have developed an automated AD …
Classification of normal and depressed EEG signals based on centered correntropy of rhythms in empirical wavelet transform domain
A widespread brain disorder of present days is depression which influences 264 million of
the world's population. Depression may cause diverse undesirable consequences, including …
the world's population. Depression may cause diverse undesirable consequences, including …
EEG based depression recognition using improved graph convolutional neural network
J Zhu, C Jiang, J Chen, X Lin, R Yu, X Li… - Computers in Biology and …, 2022 - Elsevier
Depression is a global psychological disease that does serious harm to people. Traditional
diagnostic method of the doctor-patient communication, is not objective and accurate …
diagnostic method of the doctor-patient communication, is not objective and accurate …