AIMC Topic: Adolescent

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Familial Differences in Personal PM Exposure within a Rural African Community Explained with Spatiotemporal Exposure Apportionment.

Environmental science & technology
Exposure to fine particulate matter (PM) from solid-fuel combustion is a major determinant of global morbidity and mortality. However, variations in exposure remain uncertain across many high-risk populations. This work describes personal PM exposure...

Deep learning for pediatric chest x-ray diagnosis: Repurposing a commercial tool developed for adults.

PloS one
The number of commercially available artificial intelligence (AI) tools to support radiological workflows is constantly increasing, yet dedicated solutions for children are largely unavailable. Here, we repurposed an AI-tool developed for chest radio...

Accuracy and acceptability of self-sampling HPV testing in cervical cancer screening: a population-based study in rural Yunnan, China.

Scientific reports
To evaluate the accuracy and acceptability of self-sampling samples for HPV testing for cervical cancer screening in rural Yunnan of China. In 2022, 3000 women aged 17-69 were recruited and provided self-sampling vaginal samples alongside provider-sa...

Prevalence of malnutrition and associated factors in Chinese children and adolescents aged 3-14 years using machine learning algorithms.

Journal of global health
BACKGROUND: Child malnutrition represents a critical global public health issue and it is characterised by high prevalence and severe long-term consequences for growth and development. A better understanding of its contributory factors is essential t...

Artificial intelligence platform to predict children's hospital care for respiratory disease using clinical, pollution, and climatic factors.

Journal of global health
BACKGROUND: Hospitals and health care systems may benefit from artificial intelligence (AI) and big data to analyse clinical information combined with external sources. Machine learning, a subset of AI, uses algorithms trained on data to generate pre...

An illustration of multi-class roc analysis for predicting internet addiction among university students.

PloS one
The internet is one of the essential tools today, and its impact is particularly felt among university students. Internet addiction (IA) has become a serious public health issue worldwide. This multi-class classification study aimed to identify the p...

Application of machine learning algorithms and SHAP explanations to predict fertility preference among reproductive women in Somalia.

Scientific reports
Fertility preferences significantly influence population dynamics and reproductive health outcomes, particularly in low-resource settings, such as Somalia, where high fertility rates and limited healthcare infrastructure pose significant challenges. ...

Plasma proteomics for biomarker discovery in childhood tuberculosis.

Nature communications
Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of TB as a leading cause of death in children. Current TB diagnostic assays have poor performance in children, thus a global priority is the identificati...

Future Me, a Prospection-Based Chatbot to Promote Mental Well-Being in Youth: Two Exploratory User Experience Studies.

JMIR formative research
BACKGROUND: Digital interventions have been proposed as a solution to meet the growing demand for mental health support. Large language models (LLMs) have emerged as a promising technology for creating more personalized and adaptive mental health cha...

An AI-assisted tool for automated growth monitoring in pediatric achondroplasia.

European journal of pediatrics
UNLABELLED: Growth assessment in achondroplasia requires disorder-specific growth charts incorporating sex- and age-specific values. Manual calculations are tedious and subject to error. We present an artificial intelligence (AI)-assisted tool that a...