[HTML][HTML] Application of data fusion for automated detection of children with developmental and mental disorders: A systematic review of the last decade
Mental health is a basic need for a sustainable and developing society. The prevalence and
financial burden of mental illness have increased globally, and especially in response to …
financial burden of mental illness have increased globally, and especially in response to …
An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future …
Schizophrenia (SZ) is a mental disorder that typically emerges in late adolescence or early
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior …
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior …
Automatic diagnosis of schizophrenia in EEG signals using CNN-LSTM models
Schizophrenia (SZ) is a mental disorder whereby due to the secretion of specific chemicals
in the brain, the function of some brain regions is out of balance, leading to the lack of …
in the brain, the function of some brain regions is out of balance, leading to the lack of …
A hybrid deep neural network for classification of schizophrenia using EEG Data
J Sun, R Cao, M Zhou, W Hussain, B Wang, J Xue… - Scientific Reports, 2021 - nature.com
Schizophrenia is a serious mental illness that causes great harm to patients, so timely and
accurate detection is essential. This study aimed to identify a better feature to represent …
accurate detection is essential. This study aimed to identify a better feature to represent …
[HTML][HTML] Information fusion and artificial intelligence for smart healthcare: a bibliometric study
With the fast progress in information technologies and artificial intelligence (AI), smart
healthcare has gained considerable momentum. By using advanced technologies like AI …
healthcare has gained considerable momentum. By using advanced technologies like AI …
Deep learning in physiological signal data: A survey
Deep Learning (DL), a successful promising approach for discriminative and generative
tasks, has recently proved its high potential in 2D medical imaging analysis; however …
tasks, has recently proved its high potential in 2D medical imaging analysis; however …
Artificial intelligence for brain diseases: A systematic review
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …
analyzing complex medical data and extracting meaningful relationships in datasets, for …
Transfer learning with deep convolutional neural network for automated detection of schizophrenia from EEG signals
Schizophrenia (SZ) is a severe disorder of the human brain which disturbs behavioral
characteristics such as interruption in thinking, memory, perception, speech and other living …
characteristics such as interruption in thinking, memory, perception, speech and other living …
Complex networks and deep learning for EEG signal analysis
Electroencephalogram (EEG) signals acquired from brain can provide an effective
representation of the human's physiological and pathological states. Up to now, much work …
representation of the human's physiological and pathological states. Up to now, much work …
[HTML][HTML] Internet of medical things and trending converged technologies: A comprehensive review on real-time applications
Abstract The Internet of Medical Things (IoMT) facilitates patients with all-time-connected
medical devices through cost-effective solutions and a feeling of comfort with round-the …
medical devices through cost-effective solutions and a feeling of comfort with round-the …