Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …

Importance Neuroimaging-based artificial intelligence (AI) diagnostic models have
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …

Feature selection can improve the accuracy of machine-learning models, but appropriate
steps must be taken to avoid overfitting. Nested cross-validation (nCV) is a common …

Background The development of machine learning models for aiding in the diagnosis of
mental disorder is recognized as a significant breakthrough in the field of psychiatry …

Abstract Functional Magnetic Resonance Imaging (fMRI) is presently one of the most
popular techniques for analysing the dynamic states in brain images using various kinds of …

Drug abuse is a serious problem worldwide. Owing to intermittent intake of certain
substances and the early inconspicuous clinical symptoms, this brings huge challenges for …

The application of machine-learning models to substance use disorder data shows
significant promise, with some use cases and data types showing high predictive accuracy …

Background Meditation apps have surged in popularity in recent years, with an increasing
number of individuals turning to these apps to cope with stress, including during the COVID …

Background Nicotine and illicit stimulants are very addictive substances. Although
associations between grey matter and dependence on stimulants have been frequently …

Substance use disorder (SUD) is a type of addictive encephalopathy resulting from drug
abuse, which leads to abnormal cerebral alterations indicating neurotoxicity that is …