AIMC Topic: Adolescent

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Machine learning for classification of pediatric bipolar disorder with and without psychotic symptoms based on thalamic subregional structural volume.

BMC psychiatry
BACKGROUND: The thalamus plays a crucial role in sensory processing, emotional regulation, and cognitive functions, and its dysregulation may be implicated in psychosis. The aim of the present study was to examine the differences in thalamic subregio...

Detection of Depressive Symptoms in College Students Using Multimodal Passive Sensing Data and Light Gradient Boosting Machine: Longitudinal Pilot Study.

JMIR formative research
BACKGROUND: Depression is the top contributor to global disability. Early detection of depression and depressive symptoms enables timely intervention and reduces their physical and social consequences. Prevalence estimates of depression approach 30% ...

An interpretable deep learning approach for autism spectrum disorder detection in children using NASNet-mobile.

Biomedical physics & engineering express
Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder featuring impaired social interactions and communication abilities engaging the individuals in a restrictive or repetitive behaviour. Though incurable early detection and in...

Analysis of IPV success treatment from an AI approach.

PloS one
Intimate partner violence (IPV) is a serious social problem in Chile. Understanding the patterns of internalization and the motivations maintaining it is crucial to design optimal treatments that ensure adherence and completeness. This, in addition, ...

A Deep Learning-Based Artificial Intelligence Model Assisting Thyroid Nodule Diagnosis and Management: Pilot Results for Evaluating Thyroid Malignancy in Pediatric Cohorts.

Thyroid : official journal of the American Thyroid Association
Artificial intelligence (AI) models have shown promise in predicting malignant thyroid nodules in adults; however, research on deep learning (DL) for pediatric cases is limited. We evaluated the applicability of a DL-based model for assessing thyroi...

Evaluation of sports training methods and technical characteristics based on multi-dimensional driving fuzzy intelligent computing.

PloS one
To improve the competitive state of badminton athletes and summarize the technical characteristics of badminton players, this paper introduces multi-dimensional fuzzy removal intelligent computing. Taking 120 badminton students from a sports school a...

Imitation of complex whole-body sequence in profoundly hearing-impaired adolescents.

Human movement science
Many studies have identified specific visual advantages in deaf individuals. However, few studies have linked these advantages to motor learning. This study aimed to compare the differences in movement and learning processes between profoundly hearin...

Deep learning reconstruction for T2-weighted and contrast-enhanced T1-weighted magnetic resonance enterography imaging in patients with Crohn's disease: Assessment of image quality and clinical utility.

Clinical imaging
PURPOSE: To investigate the image quality of deep learning-reconstructed T2-weighted half-Fourier single-shot turbo spin echo (DL T2 HASTE) and contrast-enhanced T1-weighted volumetric interpolated breath-hold examination (DL T1 VIBE) of magnetic res...

A qualitative analysis of college students' interest in mHealth solutions.

Frontiers in public health
This study explores college students' perceptions of an AI-driven mHealth application designed to promote well-being. With rising mental health challenges in academic settings, students increasingly seek digital tools that provide holistic support fo...

Associations of greenhouse gases, air pollutants and dynamics of scrub typhus incidence in China: a nationwide time-series study.

BMC public health
BACKGROUND: Environmental factors have been identified as significant risk factors for scrub typhus. However, the impact of inorganic compounds such as greenhouse gases and air pollutants on the incidence of scrub typhus has not been evaluated.