AIMC Topic: Child, Preschool

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Comprehensive analysis and experimental validation of BST1 as a novel diagnostic biomarker for pediatric sepsis using multiple machine learning algorithms.

European journal of pediatrics
Bone marrow stromal cell antigen-1 (BST1) expression is elevated in a variety of human diseases, but its relationship with pediatric sepsis is unclear. This study aimed to investigate the expression of BST1 in pediatric sepsis patients and its value ...

Expert-level differentiation of incomplete Kawasaki disease and pneumonia from echocardiography via multiple large receptive attention mechanisms.

Computers in biology and medicine
BACKGROUND: Incomplete Kawasaki disease (KD) is challenging to diagnose due to its lack of classic clinical features, yet it has a higher incidence of coronary artery lesions, making early detection crucial. Echocardiography plays a vital role in ide...

Changes in Epidemiological Characteristics of Varicella and Breakthrough Cases in Ningbo, China, From 2010 to 2023: Surveillance Study.

JMIR public health and surveillance
BACKGROUND: Varicella is a prevalent respiratory infectious disease. Continuous monitoring is essential to understand evolving epidemiological patterns, particularly given the impact of vaccination and recent nonpharmacological interventions.

Automated sex and age estimation from orthopantomograms using deep learning: A comparison with human predictions.

Forensic science international
INTRODUCTION/OBJECTIVES: Estimating sex and chronological age is crucial in forensic dentistry and forensic identification. Traditional manual methods for sex and age estimation are labor-intensive, time-consuming, and prone to errors. This study aim...

Rate of brain aging associates with future executive function in Asian children and older adults.

eLife
Brain age has emerged as a powerful tool to understand neuroanatomical aging and its link to health outcomes like cognition. However, there remains a lack of studies investigating the rate of brain aging and its relationship to cognition. Furthermore...

Air Pollution and Autism Spectrum Disorder: Unveiling Multipollutant Risks and Sociodemographic Influences in California.

Environmental health perspectives
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevalence worldwide. Air pollution may be a major contributor to the rise in ASD cases. This study investigated how the risk of ASD associated with prenatal...

Identifying determinants of under-5 mortality in Bangladesh: A machine learning approach with BDHS 2022 data.

PloS one
BACKGROUND: Under-5 mortality in Bangladesh remains a critical indicator of public health and socio-economic development. Traditional methods often struggle to capture the complex, non-linear relationships influencing under-5 mortality. This study le...

Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki disease.

Italian journal of pediatrics
BACKGROUND: Kawasaki disease (KD) is a leading cause of acquired heart disease in children that is treated with intravenous immunoglobulin (IVIG). However, 10-20% of cases exhibit IVIG resistance, which increases the risk of coronary complications. E...

Interpretable machine learning models for predicting childhood myopia from school-based screening data.

Scientific reports
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 ...

Use of Transfer Learning for the Automated Segmentation and Detection of Swallows via Digital Cervical Auscultation in Children.

Dysphagia
Digital cervical auscultation (CA) has high diagnostic test accuracy in the detection of aspiration in children. However, the clinical application of digital CA is limited because swallow sound recordings require manual segmentation by trained expert...