AIMC Topic: Adolescent

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AI-driven analysis of diabetes risk determinants in U.S. adults: Exploring disease prevalence and health factors.

PloS one
BACKGROUND: Diabetes remains a major public health concern in the United States, with a complex interplay of behavioral, demographic, and clinical risk factors. This study aims to identify the three best-performing machine learning models for diabete...

Pulmonary Embolism Survival Prediction Using Multimodal Learning Based on Computed Tomography Angiography and Clinical Data.

Journal of thoracic imaging
PURPOSE: Pulmonary embolism (PE) is a significant cause of mortality in the United States. The objective of this study is to implement deep learning (DL) models using computed tomography pulmonary angiography (CTPA), clinical data, and PE Severity In...

Development of the Screen for Child Anxiety Related Emotional Disorders (SCARED) optimal short scale for Chinese children and adolescents: based on FasterRisk machine learning modeling.

BMC public health
BACKGROUND: Although the Screen for Child Anxiety Related Emotional Disorders (SCARED) is a widely used tool for assessing anxiety, its 41-item format makes it a time-intensive method for identifying children and adolescents at high risk of anxiety. ...

Development of the generative artificial intelligence awareness scale for secondary school students in Türkiye.

European journal of pediatrics
The widespread adoption of generative artificial intelligence (AI) in education and daily life necessitates a deeper understanding of students' awareness and attitudes. However, there is a lack of appropriate and psychometrically validated tools to a...

Effects of attractions and social attributes on peoples' usage intention and media dependence towards chatbot: The mediating role of parasocial interaction and emotional support.

BMC psychology
PURPOSE: It is important to explore the relationship between humans and chatbots to improve human-robot interaction in the era of artificial intelligence. This study aims to explore the effects of attractions and social attributes of chatbots on user...

Integrating multiple feature assessment methods to identify key predictors of repeat suicide attempts in Taiwan.

BMC psychiatry
BACKGROUND: The high rate of repeat attempts among individuals who have previously attempted suicide presents a critical challenge in public health and suicide prevention. While early and targeted intervention is crucial for this high-risk group, eff...

Assessment of university students' earthquake coping strategies using artificial intelligence methods.

Scientific reports
Earthquakes are one of the most destructive natural disasters that pose a serious threat to human life and infrastructure worldwide. The aim of this study is to evaluate the coping strategies of adult individuals in Turkey regarding earthquake stress...

Using deep learning to predict internalizing problems from brain structure in youth.

Translational psychiatry
Internalizing problems (e.g., anxiety and depression) are associated with a wide range of adverse outcomes. While some predictors of internalizing problems are known (e.g., their frequent co-occurrence with neurodevelopmental (ND) conditions), the bi...

Recognizing Skateboard and Kickboard Commuting Behaviors Using Activity Trackers: Feasibility Study Using Machine Learning Approaches.

JMIR formative research
BACKGROUND: Active commuting, such as skateboarding and kickboarding, is gaining popularity as an alternative to traditional modes of transportation such as walking and cycling. However, current activity trackers and smartphones, which rely on accele...

Effect of a Cognitive Behavioral Therapy-Based AI Chatbot on Depression and Loneliness in Chinese University Students: Randomized Controlled Trial With Financial Stress Moderation.

JMIR mHealth and uHealth
BACKGROUND: Mental health concerns are prevalent among university students, with financial stress further compounding these issues. While cognitive behavioral therapy (CBT) is effective for these conditions, its delivery through artificial intelligen...