Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging
Autism spectrum disorder (ASD) is a neurodevelopmental incurable disorder with a long
diagnostic period encountered in the early years of life. If diagnosed early, the negative …
diagnostic period encountered in the early years of life. If diagnosed early, the negative …
[HTML][HTML] Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis
Electroencephalography (EEG) is an important tool for studying the human brain activity and
epileptic processes in particular. EEG signals provide important information about …
epileptic processes in particular. EEG signals provide important information about …
Diagnostic of autism spectrum disorder based on structural brain MRI images using, grid search optimization, and convolutional neural networks
In this study, an automatic autism diagnostic model based on sMRI is proposed. This
proposed model consists of two basic stages. The first stage is the preprocessing stage …
proposed model consists of two basic stages. The first stage is the preprocessing stage …
A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG
Autism spectrum disorder (ASD) is a developmental disability characterized by persistent
impairments in social interaction, speech and nonverbal communication, and restricted or …
impairments in social interaction, speech and nonverbal communication, and restricted or …
Application of entropy measures on intrinsic mode functions for the automated identification of focal electroencephalogram signals
The brain is a complex structure made up of interconnected neurons, and its electrical
activities can be evaluated using electroencephalogram (EEG) signals. The characteristics …
activities can be evaluated using electroencephalogram (EEG) signals. The characteristics …
Frequency recognition in SSVEP-based BCI using multiset canonical correlation analysis
Canonical correlation analysis (CCA) has been one of the most popular methods for
frequency recognition in steady-state visual evoked potential (SSVEP)-based brain …
frequency recognition in steady-state visual evoked potential (SSVEP)-based brain …
Autism: cause factors, early diagnosis and therapies
Autism spectrum disorder (ASD) is a complex neurobiological disorder characterized by
neuropsychological and behavioral deficits. Cognitive impairment, lack of social skills, and …
neuropsychological and behavioral deficits. Cognitive impairment, lack of social skills, and …
Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals
UR Acharya, SV Sree, PCA Ang, R Yanti… - International journal of …, 2012 - World Scientific
Epilepsy, a neurological disorder, is characterized by the recurrence of seizures.
Electroencephalogram (EEG) signals, which are used to detect the presence of seizures, are …
Electroencephalogram (EEG) signals, which are used to detect the presence of seizures, are …
EEG signal analysis for diagnosing neurological disorders using discrete wavelet transform and intelligent techniques
Analysis of electroencephalogram (EEG) signals is essential because it is an efficient
method to diagnose neurological brain disorders. In this work, a single system is developed …
method to diagnose neurological brain disorders. In this work, a single system is developed …
EEG classification of ADHD and normal children using non-linear features and neural network
Abstract Purpose Attention-Deficit Hyperactivity Disorder (ADHD) is a neuro-developmental
disorder that is characterized by hyperactivity, inattention and abrupt behaviors. This study …
disorder that is characterized by hyperactivity, inattention and abrupt behaviors. This study …