AIMC Topic: Child, Preschool

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Clinical outcome prediction in pediatric respiratory infections using hybrid feature selection and a genetic algorithm-optimized machine learning.

Scientific reports
Respiratory ailments constitute various pathological conditions affecting the respiratory system, including the airways, pulmonary tissues, and associated structures. When these conditions are left untreated or inadequately managed, they can result i...

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...

Feasibility of machine learning analysis for the identification of patients with possible primary ciliary dyskinesia.

Orphanet journal of rare diseases
BACKGROUND: Significant diagnostic delays are common in primary ciliary dyskinesia (PCD), a rare disease that is significantly underdiagnosed. Scalable screening methods could improve early identification and health outcomes.

Predicting outcomes in pediatric patients with acute kidney injury: a retrospective single-center cohort study using machine learning models.

BMC medical informatics and decision making
OBJECTIVE: To develop and evaluate machine learning models combined with survival analysis for predicting 7-, 14-, and 28-day mortality in critically ill children with acute kidney injury (AKI), identifying key predictors to guide risk stratification...

Predictive modeling of adaptive behavior trajectories in autism: insights from a clinical cohort study.

Translational psychiatry
Research aimed at understanding how baseline clinical and demographic characteristics influence outcomes over time is critically important to inform individualized therapeutic programs for children with neurodevelopmental differences. This study char...

Clinical, biochemical, and molecular characterization of a cohort of Egyptian patients with Sanfilippo B syndrome (MPS IIIB): Bayesian Gaussian mixture model.

Molecular biology reports
BACKGROUND: Lysosomal storage diseases (LSDs) are a group of genetically heterogeneous inherited metabolic disorders that affect the functions of the lysosomes in different human tissues. Mucopolysaccharidosis IIIB (MPS IIIB), Sanfilippo B syndrome, ...

A machine learning-based predictive model for multilobar pulmonary consolidation induced by macrolide-resistant pneumonia caused by the 23S rRNA A2063G mutation.

Microbiology spectrum
This study aims to develop a machine learning (ML)-based predictive model for assessing the risk of multilobar pulmonary consolidation in children with macrolide-resistant pneumonia (MRMP) caused by the 23S rRNA A2063G mutation, a subgroup underrepr...

AI-driven prognostics in pediatric bone marrow transplantation: a CAD approach with Bayesian and PSO optimization.

BMC medical informatics and decision making
Bone marrow transplantation (BMT) is a critical treatment for various hematological diseases in children, offering a potential cure and significantly improving patient outcomes. However, the complexity of matching donors and recipients and predicting...

Development and validation of diagnostic and prognostic prediction tools for dental caries in young children through prospective and cross-sectional observational studies: a protocol.

BMJ open
INTRODUCTION: Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection and impaired quality of life. Early prevention is a key strategy for reducing the prevalence of dental car...