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Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …
problems for people with a detrimental effect on the functioning of the nervous system. In …
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 …
Deep learning for neuroimaging-based diagnosis and rehabilitation of autism spectrum disorder: a review
Abstract Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …
Removing independent noise in systems neuroscience data using DeepInterpolation
Progress in many scientific disciplines is hindered by the presence of independent noise.
Technologies for measuring neural activity (calcium imaging, extracellular electrophysiology …
Technologies for measuring neural activity (calcium imaging, extracellular electrophysiology …
The evolution of Big Data in neuroscience and neurology
L Dipietro, P Gonzalez-Mego, C Ramos-Estebanez… - Journal of Big Data, 2023 - Springer
Neurological diseases are on the rise worldwide, leading to increased healthcare costs and
diminished quality of life in patients. In recent years, Big Data has started to transform the …
diminished quality of life in patients. In recent years, Big Data has started to transform the …
ADD-Net: an effective deep learning model for early detection of Alzheimer disease in MRI scans
Alzheimer's Disease (AD) is a neurological brain disorder marked by dementia and
neurological dysfunction that affects memory, behavioral patterns, and reasoning …
neurological dysfunction that affects memory, behavioral patterns, and reasoning …
[HTML][HTML] Dad-net: Classification of alzheimer's disease using adasyn oversampling technique and optimized neural network
Alzheimer's Disease (AD) is a neurological brain disorder that causes dementia and
neurological dysfunction, affecting memory, behavior, and cognition. Deep Learning (DL), a …
neurological dysfunction, affecting memory, behavior, and cognition. Deep Learning (DL), a …
Increased connectivity of pain matrix in chronic migraine: a resting-state functional MRI study
Objective To investigate the whole-brain resting-state functional connectivity in patients with
chronic migraine (CM) using a data-driven method. Methods We prospectively recruited …
chronic migraine (CM) using a data-driven method. Methods We prospectively recruited …
Towards artificial intelligence in mental health: a comprehensive survey on the detection of schizophrenia
Abstract Computer Aided Diagnosis systems assist radiologists and doctors in the early
diagnosis of mental disorders such as Alzheimer's, bipolar disorder, depression, autism …
diagnosis of mental disorders such as Alzheimer's, bipolar disorder, depression, autism …
An expanding manifold in transmodal regions characterizes adolescent reconfiguration of structural connectome organization
Adolescence is a critical time for the continued maturation of brain networks. Here, we
assessed structural connectome development in a large longitudinal sample ranging from …
assessed structural connectome development in a large longitudinal sample ranging from …