Neurological diseases are on the rise worldwide, leading to increased healthcare costs and
diminished quality of life in patients. In recent years, Big Data has started to transform the�…

The role of functional magnetic resonance imaging (fMRI) is assuming an increasingly
central role in autism diagnosis. The integration of Artificial Intelligence (AI) into the realm of�…

Migraine is a burdensome neurological disorder that still lacks clear and easily accessible
diagnostic biomarkers. Furthermore, a straightforward pathway is hard to find for�…

Abstract Chronic Painful Temporomandibular Disorders (TMD) are challenging to diagnose
and manage due to their complexity and lack of understanding of brain mechanism. In the�…

Many functional magnetic resonance imaging (fMRI) studies and presurgical mapping
applications rely on mass-univariate inference with subsequent multiple comparison�…

Over the past decade, the intricacies of sports-related concussions among female athletes
have become readily apparent. Traditional clinical methods for diagnosing concussions�…

Functional near-infrared spectroscopy (fNIRS) and its interaction with machine learning (ML)
is a popular research topic for the diagnostic classification of clinical disorders due to the�…

Objective There is a growing interest in functional near-infrared spectroscopy (fNIRS) among
researchers due to its remarkable advantages such as ease of use, being inexpensive and�…

While mainstream clinical techniques for functional imaging of the brain such as BOLD
(blood oxygenation level dependent) fMRI (functional magnetic resonance imaging)�…

In this work, we aim to give a thorough treatment of artificial intelligence in the domain of
molecular neuroimaging. It will be divided into 3 broad portions. First, we will give a brief�…