AIMC Topic: Adolescent

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Utilizing multi-level convolutional neural networks to achieve refined modeling and visual analysis of college students' mental health data.

PloS one
Early identification of students' mental health issues has become an urgent priority in education and public health. However, existing studies often rely on questionnaire-based assessments or traditional machine learning models, which are limited by ...

Invasive meningococcal disease in adolescents in Europe and select geographies: Disease burden, unmet medical need, and optimizing prevention.

Human vaccines & immunotherapeutics
Invasive meningococcal disease (IMD) is uncommon but serious; the case fatality rate is 8-15% and up to 20-40% of survivors experience disabling sequelae, with a substantial socioeconomic impact. Although incidence is highest in infants and young chi...

Alterations of multilayer network correlated with cognitive impairment and gene expression profiles in children with idiopathic generalized epilepsy.

Scientific reports
This study investigated dynamic brain network changes and their genetic correlations in children with idiopathic generalized epilepsy (IGE). We included 26 children with IGE and 35 healthy controls, all participants underwent resting-state functional...

Association between exposure to PM and black carbon and the risk of childhood leukemia in Tehran: A case-control study with critical exposure time windows.

Environmental research
Limited research has explored the relationship between air pollutants and childhood leukemia during critical exposure periods, and no such research has been conducted in Tehran to date. This study assessed the association between exposure to fine par...

Machine learning improves detection of alpha thalassemia carriers compared to clinical features.

Scientific reports
Alpha-thalassemia is a widespread genetic disorder, and accurately distinguishing between alpha-plus (α⁺) and alpha-zero (α⁰) types is critical for effective screening and management. This study developed and evaluated machine learning models to clas...

Age-specific prevalence and predictors of lifetime suicide attempts using machine learning in Chinese adults: a nationwide multi-centre survey.

Epidemiology and psychiatric sciences
AIMS: The epidemiology and age-specific patterns of lifetime suicide attempts (LSA) in China remain unclear. We aimed to examine age-specific prevalence and predictors of LSA among Chinese adults using machine learning (ML).

The influence of human agency beliefs on ascribing gaze-signalled communicative intent.

Scientific reports
Communication with artificial agents, such as virtual characters and social robots, is becoming more prevalent, making it crucial to understand how their behaviours can best support social interaction. Eye gaze is a key communicative behaviour, as it...

Bio-inspired neutrosophic-enzyme intelligence framework for pediatric dental disease detection using multi-modal clinical data.

Scientific reports
Pediatric oral diseases affect over 60% of children globally, yet current diagnostic approaches lack precision and speed necessary for early intervention. This study developed a novel bio-inspired neutrosophic-enzyme intelligence framework integratin...

Rapid and accurate prediction of cycloplegic refraction in Chinese children: development and validation of machine learning models.

Journal of global health
BACKGROUND: Uncorrected refractive error affects approximately 19 million children globally, resulting in preventable vision loss. However, cycloplegic refraction, the gold standard for assessment, remains largely inaccessible in low-resource setting...

Development of machine learning-based mpox surveillance models in a learning health system.

Sexually transmitted infections
OBJECTIVES: This study aimed to develop robust machine learning (ML)-based and deep learning (DL)-based models capable of detecting mpox cases for surveillance efforts using clinical notes.