INTRODUCTION: Autism Spectrum Disorder (ASD) presents significant challenges in social communication and interaction, critically impacting the lives of children with ASD. Traditional interventions, such as Applied Behavior Analysis (ABA) and Social S...
BACKGROUND: Diagnosing bipolar disorder poses a challenge in clinical practice and demands a substantial time investment. With the growing utilization of artificial intelligence in mental health, researchers are endeavoring to create AI-based diagnos...
INTRODUCTION: It is important to consider individual differences in research on educational technology. This study investigates the interplay between autistic traits, gender, and the perception of artificial intelligence (AI) tools designed for secon...
Autism Spectrum Disorder (ASD) affects millions of individuals worldwide, presenting challenges in social communication, repetitive behaviors, and sensory processing. Despite its prevalence, diagnosis can be lengthy, and access to appropriate treatme...
BACKGROUND: We previously reported that machine learning could be used to predict conversion to psychosis in individuals at clinical high risk (CHR) for psychosis with up to 90% accuracy using the North American Prodrome Longitudinal Study-3 (NAPLS-3...
INTRODUCTION: Evaluating neurocognitive functions and diagnosing psychiatric disorders in older adults is challenging due to the complexity of symptoms and individual differences. An innovative approach that combines the accuracy of artificial intell...
BACKGROUND: Stress is a significant risk factor for psychiatric disorders such as major depressive disorder (MDD) and panic disorder (PD). This highlights the need for advanced stress-monitoring technologies to improve treatment. Stress affects the a...
INTRODUCTION: Machine learning (ML) is an effective tool for predicting mental states and is a key technology in digital psychiatry. This study aimed to develop ML algorithms to predict the upper tertile group of various anxiety symptoms based on mul...