AIMC Topic: Child, Preschool

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Epigenomic diagnosis and prognosis of Acute Myeloid Leukemia.

Nature communications
Despite the critical role of DNA methylation, clinical implementations harnessing its promise have not been described in acute myeloid leukemia. Utilizing DNA methylation from 3314 leukemia patient samples across 11 harmonized cohorts, we describe th...

The potential of machine learning in classifying relapse and non-relapse in children with clubfoot based on movement patterns.

Scientific reports
The diverse nature and timing of a clubfoot relapse pose challenges for early detection. A relapsed clubfoot typically involves a combination of deformities affecting a child's movement pattern across multiple joint levels, formed by a complex kinema...

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...

MDNCT: a multi-domain neurocognitive transformer architecture approach for early prediction of autism spectrum disorders.

Scientific reports
Intellectual disability (ID) refers to a disorder involving intelligence and adaptive behavior that meets specific criteria involving deviance from the norm in terms of degree. ID is more common in males than females, and the causes can be genetic or...

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...

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...

EEG microstate analysis in children with prolonged disorders of consciousness.

Scientific reports
Prolonged disorders of consciousness (pDoC) in children lack objective and effective diagnostic methods to assess consciousness states, hindering targeted treatment selection and delaying recovery. It remains unclear whether EEG microstate analysis, ...

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...