Purpose To perform a systematic review on the research on the application of artificial
intelligence (AI) to imaging published in Italy and identify its fields of application, methods …

A complete understanding of the brain requires an integrated description of the numerous
scales and levels of neural organization. This means studying the interplay of genes and …

In clinical practice, several standardized neuropsychological tests have been designed to
assess and monitor the neurocognitive status of patients with neurodegenerative diseases …

In recent years, several studies have demonstrated that machine learning and deep learning
systems can be very useful to accurately predict brain age. In this work, we propose a novel …

Dynamic functional connectivity (DFC) was established in the past decade as a potent
approach to reveal non-trivial, time-varying properties of neural interactions–such as their …

Morphological changes in the brain over the lifespan have been successfully described by
using structural magnetic resonance imaging (MRI) in conjunction with machine learning …

Malignant pleural mesothelioma (MPM) is a rare neoplasm, mainly caused by asbestos
exposure, with a high mortality rate. The management of patients with MPM is controversial …

Signal processing and machine learning techniques are changing the clinical practice
based on medical imaging from many perspectives. A major topic is related to (i) the …

Abstract We construct Functional Connectivity Networks (FCN) from resting state fMRI
(rsfMRI) recordings towards the classification of brain activity between healthy and …

HIV is associated with disruptions in cognition and brain function. Marijuana use is highly
prevalent in HIV but its effects on resting brain function in HIV are unknown. Brain function …