AIMC Topic: Child, Preschool
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Explainable AI for enhanced accuracy in malaria diagnosis using ensemble machine learning models.
BMC medical informatics and decision making
Apr 11, 2025
BACKGROUND: Malaria, an infectious disease caused by protozoan parasites belonging to the Plasmodium genus, remains a significant public health challenge, with African regions bearing the heaviest burden. Machine learning techniques have shown great ...
Children on wheels: Identifying crash determinants using cluster correspondence analysis.
Accident; analysis and prevention
Apr 10, 2025
Child bicyclists (14 years old and younger) are among the most vulnerable road users, facing significant risks of crashes that often result in severe injuries or fatalities. This study aims to identify key factors influencing child bicyclist crashes ...
Using fuzzy decision support to create a positive mental health environment for preschoolers.
Scientific reports
Apr 10, 2025
The preschool period is a crucial time for behavioural and social-emotional development and the cultivation of mental well-being. Preschoolers may be affected by various traumatic problems. During this process, preschoolers may develop hazardous beha...
Exploring cortical excitability in children with cerebral palsy through lower limb robot training based on MI-BCI.
Scientific reports
Apr 10, 2025
This study aims to compare brain activity differences under the motor imagery-brain-computer interface (MI-BCI), motor imagery (MI), and resting (REST) paradigms through EEG microstate and functional connectivity (FC) analysis, providing a theoretica...
Prediction of outpatient visits for allergic rhinitis using an artificial intelligence LSTM model - a study in Eastern China.
BMC public health
Apr 9, 2025
BACKGROUND: Allergic rhinitis is a common disease that can affect the health of patients and bring huge social and economic burdens. In this study, we developed a model to predict the incidence rate of allergic rhinitis so as to provide accurate info...
The potential of evaluating shape drawing using machine learning for predicting high autistic traits.
PloS one
Apr 9, 2025
BACKGROUND: Children with high autistic traits often exhibit deficits in drawing, an important skill for social adaptability. Machine learning is a powerful technique for learning predictive models from movement data, so drawing processes and product...
A comparison of neural networks and regression-based approaches for estimating kidney function in pediatric chronic kidney disease: Practical predictive epidemiology for clinical management of a progressive disease.
Annals of epidemiology
Apr 8, 2025
PURPOSE: Clinical management of pediatric chronic kidney disease requires estimation of glomerular filtration rate (eGFR). Currently, eGFR is determined by two endogenous markers measured in blood: serum creatine (SCr) and cystatin C (CysC). Machine ...
Leveraging artificial intelligence for diagnosis of children autism through facial expressions.
Scientific reports
Apr 8, 2025
The global population contains a substantial number of individuals who experience autism spectrum disorder, thus requiring immediate identification to enable successful intervention approaches. The authors assess the detection of autism-related learn...
Improving image quality on pediatric and neonatal radiography using AI-based compensation for image degradation.
Japanese journal of radiology
Apr 7, 2025
PURPOSE: To evaluate the impact of an AI-based, noise reduction technique for compensation of image degradation on pediatric and neonatal chest and abdomen radiography using a visual grading analysis.
Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.
Scientific reports
Apr 7, 2025
Early diagnosis and access to resources, support and therapy are critical for improving long-term outcomes for children with autism spectrum disorder (ASD). ASD is typically detected using a case-finding approach based on symptoms and family history,...
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