With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …

Abstract Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …

Brain-machine interfaces (BMIs) can be used to decode brain activity into commands to
control external devices. This paper presents the decoding of intuitive upper extremity …

Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and
symptoms that appear in early childhood. ASD is also associated with communication …

Objective: We exploit altered patterns in brain functional connectivity as features for
automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have …

While convolutional neural network (CNN) has been demonstrating powerful ability to learn
hierarchical spatial features from medical images, it is still difficult to apply it directly to …

Deep-learning models have enabled performance leaps in analysis of high-dimensional
functional MRI (fMRI) data. Yet, many previous methods are suboptimally sensitive for …

The need for time and attention given by the doctor to the patient, due to the increased
volume of medical data to be interpreted and filtered for diagnostic and therapeutic purposes …

The commonly used classifiers for pattern recognition of human motion, like
backpropagation neural network (BPNN) and support vector machine (SVM), usually …

In recent years, brain imaging technology has become a hot topic within the field of
neuroscience. Such technology includes functional Magnetic Resonance Imaging (fMRI)(Liu …