Application of artificial intelligence in wearable devices: Opportunities and challenges
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
Deep learning and artificial intelligence in sustainability: a review of SDGs, renewable energy, and environmental health
Artificial intelligence (AI) and deep learning (DL) have shown tremendous potential in
driving sustainability across various sectors. This paper reviews recent advancements in AI …
driving sustainability across various sectors. This paper reviews recent advancements in AI …
Emotion recognition in EEG signals using deep learning methods: A review
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …
planning, reasoning, and other mental states. As a result, they are considered a significant …
Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …
the health and well-being of millions of people worldwide. Structural and functional …
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 …
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) …
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 …
Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images
Abstract The coronavirus (COVID-19) is currently the most common contagious disease
which is prevalent all over the world. The main challenge of this disease is the primary …
which is prevalent all over the world. The main challenge of this disease is the primary …
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 …
Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies
Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
diagnosis will help the clinicians to provide accurate treatment for the patients. The …