AIMC Topic: Child, Preschool
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Interpretable machine learning models for predicting childhood myopia from school-based screening data.
Scientific reports
Jun 5, 2025
This study assessed the efficacy of various diagnostic indicators and machine learning (ML) models in predicting childhood myopia. A total of 2,365 children aged 5-12 years were included in the study. The participants were exposed to non-cycloplegic ...
An interpretable deep learning approach for autism spectrum disorder detection in children using NASNet-mobile.
Biomedical physics & engineering express
Jun 3, 2025
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...
Integrative machine learning identifies robust inflammation-related diagnostic biomarkers and stratifies immune-heterogeneous subtypes in Kawasaki disease.
Pediatric rheumatology online journal
Jun 2, 2025
BACKGROUND: Kawasaki disease (KD), a pediatric systemic vasculitis, lacks reliable diagnostic biomarkers and exhibits immune heterogeneity, complicating clinical management. Current therapies face challenges in targeting specific immune pathways and ...
Comparison of salivary statherin and beta-defensin-2 levels, oral health behaviors, and demographic factors in children with and without early childhood caries.
BMC oral health
May 31, 2025
BACKGROUND: Early childhood caries (ECC) is a widespread pediatric dental condition that is influenced by a combination of biological, behavioral, and demographic factors. Salivary biomarkers, including beta-defensin-2 (BD-2) and statherin (STATH), o...
Single-tooth resolved, whole-mouth prediction of early childhood caries via spatiotemporal variations of plaque microbiota.
Cell host & microbe
May 30, 2025
Early childhood caries (ECC) exhibits tooth specificity, highlighting the need for single-tooth-level prevention. We profiled 2,504 dental plaque microbiota samples from 89 preschoolers across two cohorts, tracking compositional changes with imputed ...
Undesired nexus poor health status of child under-five: A case study of Pakistan.
PloS one
May 30, 2025
Childhood morbidity and mortality are key indicators of human development, particularly reflecting poor health conditions in children. In Pakistan, child mortality remains a serious problem despite efforts to reduce it. One factor that may be associa...
Associations of greenhouse gases, air pollutants and dynamics of scrub typhus incidence in China: a nationwide time-series study.
BMC public health
May 29, 2025
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.
Development of a machine learning-based predictive nomogram for screening children with juvenile idiopathic arthritis: a pseudo-longitudinal study of 223,195 children in the United States.
Frontiers in public health
May 29, 2025
BACKGROUND: Juvenile idiopathic arthritis (JIA) is a prevalent chronic rheumatological condition in children, with reported prevalence ranging from 12. 8 to 45 per 100,000 and incidence rates from 7.8 to 8.3 per 100,000 person-years. The diagnosis of...
Applying exposure-response analysis to enhance Mycophenolate Mofetil dosing precision in pediatric patients with immune-mediated renal diseases by machine learning models.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
May 28, 2025
BACKGROUND: Mycophenolate mofetil (MMF), a cornerstone immunosuppressant for lupus nephritis, is increasingly used off-label in pediatric immune-mediated renal diseases. The aims of this study were to develop and validate pharmacokinetic models for m...
A pediatric ECG database with disease diagnosis covering 11643 children.
Scientific data
May 26, 2025
Electrocardiogram (ECG) is a common non-invasive diagnostic tool for cardiovascular diseases. Adequate data is crucial in utilizing deep learning to achieve intelligent diagnosis of ECG. The existing ECG datasets almost only focus on adults and most ...
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