Significance: Optical neuroimaging has become a well-established clinical and research
tool to monitor cortical activations in the human brain. It is notable that outcomes of …

Background Transfer learning is a form of machine learning where a pre-trained model
trained on a specific task is reused as a starting point and tailored to another task in a …

Deep learning algorithms have been moderately successful in diagnoses of diseases by
analyzing medical images especially through neuroimaging that is rich in annotated data …

Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders in the
world. Although there is no known cure for it at the present, preventive drug trials and …

The tumor in the brain is a serious disease that causes death in humans. Various imaging
modalities are utilized for identifying tumors, but the huge data produced by magnetic …

Introduction Conflict monitoring and processing is an important part of the human cognitive
system, it plays a key role in many studies of cognitive disorders. Methods Based on a …

This systematic review aimed to evaluate previous studies which used near-infrared
spectroscopy (NIRS) in dementia given its suitability as a diagnostic and investigative tool in …

Background Patients in minimally conscious state (MCS) exist measurable evidence of
consciousness. The frontal lobe is a crucial part of the brain that encodes abstract …

This paper develops neural network models that can recognize Parkinson's disease (PD) at
its early stage. PD is a common neurodegenerative disorder that presents with progressive …

Significance Dementia presents a global healthcare crisis, and neuroimaging is the main
method for develo** effective diagnoses and treatments. Yet currently, there is a lack of …