Neuroimaging-based single subject prediction of brain disorders has gained increasing
attention in recent years. Using a variety of neuroimaging modalities such as structural …

Neuroimaging‐based approaches have been extensively applied to study mental illness in
recent years and have deepened our understanding of both cognitively healthy and …

Neuropsychiatric disorders are diagnosed based on behavioral criteria, which makes the
diagnosis challenging. Objective biomarkers such as neuroimaging are needed, and when …

Psychiatric disorders are increasingly being recognised as having a biological basis, but
their diagnosis is made exclusively behaviourally. A promising approach for …

Motivation This study reports a framework to discriminate patients with schizophrenia and
normal healthy control subjects, based on magnetic resonance imaging (MRI) of the brain …

Evaluating various algorithms for the inter-subject registration of brain magnetic resonance
images (MRI) is a necessary topic receiving growing attention. Existing studies evaluated …

The outcome of first-episode psychosis (FEP) is highly variable, ranging from early
sustained recovery to antipsychotic treatment resistance from the onset of illness. For …

Artificial Intelligence in healthcare employs machine learning algorithms to emulate human
cognition in the analysis of complicated or large sets of data. Specifically, artificial …

To date, a large number of magnetic resonance imaging (MRI) studies have been conducted
in schizophrenia, which generally demonstrate gray matter reduction, predominantly in the …

Abstract Machine learning is a powerful tool that has previously been used to classify
schizophrenia (SZ) patients from healthy controls (HC) using magnetic resonance images …