Introduction: Clinical decision support systems (CDSSs), powered by machine learning and artificial intelligence, have demonstrated potential in clinical diagnosis intervention for neurological psychiatric disorders. Considering the importance of early detection Alzheimer’s disease (AD), this study aims to explore a data-driven non-knowledge-based CDSS predicting AD diagnoses individuals. In CD...

Most pediatric professionals do not use a systematic screening, identification, or referral process to detect serious sleep problems and disorders in children and adolescents. Therefore, only 2% to 3% of children with sleep disorders are identified and treated. This article presents a screening, referral, and diagnostic process that helps detect and correct sleep disorders that impact children'...

This study used latent variable growth curve modeling to identify predictors and correlates of verbal learning over trials on a list-learning task in patients with dementia. Data from 116 patients evaluated at the Detroit satellite of the Michigan Alzheimer's Disease Research Center were incorporated in the present analyses. Patients were administered the Fuld Object Memory Evaluation, examined...

Anxiety disorders, including generalized anxiety disorder (GAD), social anxiety disorder (SAD), and panic anxiety disorder (PAD), are a group of common psychiatric conditions. They are characterized by excessive worrying, uneasiness, and fear of future events, such that they affect social and occupational functioning. Anxiety disorders can alter behavior and cognition as well, yet little is kno...

INTRODUCTION There are no known biological measures that accurately predict future development of psychiatric disorders in individual at-risk adolescents. We investigated whether machine learning and fMRI could help to: 1. differentiate healthy adolescents genetically at-risk for bipolar disorder and other Axis I psychiatric disorders from healthy adolescents at low risk of developing these dis...