One of the most promising areas of health innovation is the application of artificial
intelligence (AI), primarily in medical imaging. This article provides basic definitions of terms …

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 …

In this chapter, we explore Support Vector Machine (SVM)—a machine learning method that
has become exceedingly popular for neuroimaging analysis in recent years. Because of …

OBJECTIVE. The purposes of this article are to describe concepts that radiologists should
understand to evaluate machine learning projects, including common algorithms …

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

Background Diagnosis of schizophrenia (SCZ) is made exclusively clinically, since specific
biomarkers that can predict the disease accurately remain unknown. Machine learning (ML) …

Abstract In the recent 5 years (2014–2018), there has been growing interest in the use of
machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic …

In recent times, microarray gene expression datasets have gained significant popularity due
to their usefulness to identify different types of cancer directly through bio-markers. These …

Background Psychotic disorders are characterized by structural and functional abnormalities
in brain networks. Neuroimaging techniques map and characterize such abnormalities using …

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