AIMC Topic: Child, Preschool
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Does machine learning improve prediction accuracy of the Endoscopic Third Ventriculostomy Success Score? A contemporary Hydrocephalus Clinical Research Network cohort study.
Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
Dec 10, 2024
PURPOSE: This Hydrocephalus Clinical Research Network (HCRN) study had two aims: (1) to compare the predictive performance of the original ETV Success Score (ETVSS) using logistic regression modeling with other newer machine learning models and (2) t...
A neural network integrated mathematical model to analyze the impact of nutritional status on cognitive development of child.
Computers in biology and medicine
Dec 9, 2024
Cognitive development is a crucial developmental aspect of children. It is a concise field of study in psychology and neuroscience that focuses on various developmental aspects of the brain. Among all other factors, nutritional status is believed to ...
Limbic/paralimbic connection weakening in preschool autism-spectrum disorder based on diffusion basis spectrum imaging.
The European journal of neuroscience
Dec 9, 2024
This study aims to investigate the value of basal ganglia and limbic/paralimbic networks alteration in identifying preschool children with ASD and normal controls using diffusion basis spectrum imaging (DBSI). DBSI data from 31 patients with ASD and ...
Revisiting the Endoscopic Third Ventriculostomy Success Score using machine learning: can we do better?
Journal of neurosurgery. Pediatrics
Dec 6, 2024
OBJECTIVE: The Endoscopic Third Ventriculostomy Success Score (ETVSS) is a useful decision-making heuristic when considering the probability of surgical success, defined traditionally as no repeat cerebrospinal fluid diversion surgery needed within 6...
Using Machine Learning to Fight Child Acute Malnutrition and Predict Weight Gain During Outpatient Treatment with a Simplified Combined Protocol.
Nutrients
Dec 6, 2024
BACKGROUND/OBJECTIVES: Child acute malnutrition is a global public health problem, affecting 45 million children under 5 years of age. The World Health Organization recommends monitoring weight gain weekly as an indicator of the correct treatment. Ho...
A machine learning-based risk score for prediction of mechanical ventilation in children with dengue shock syndrome: A retrospective cohort study.
PloS one
Dec 6, 2024
BACKGROUND: Patients with severe dengue who develop severe respiratory failure requiring mechanical ventilation (MV) support have significantly increased mortality rates. This study aimed to develop a robust machine learning-based risk score to predi...
Prediction of undernutrition and identification of its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.
PloS one
Dec 6, 2024
BACKGROUND AND OBJECTIVES: Child undernutrition is a leading global health concern, especially in low and middle-income developing countries, including Bangladesh. Thus, the objectives of this study are to develop an appropriate model for predicting ...
Accuracy of radiologists and radiology residents in detection of paediatric appendicular fractures with and without artificial intelligence.
BMJ health & care informatics
Dec 5, 2024
OBJECTIVES: We aim to evaluate the accuracy of radiologists and radiology residents in the detection of paediatric appendicular fractures with and without the help of a commercially available fracture detection artificial intelligence (AI) solution i...
Prediction of preterm birth using machine learning: a comprehensive analysis based on large-scale preschool children survey data in Shenzhen of China.
BMC pregnancy and childbirth
Dec 4, 2024
BACKGROUND: Preterm birth (PTB) is a significant cause of neonatal mortality and long-term health issues. Accurate prediction and timely prevention of PTB are essential for reducing associated child mortality and morbidity. Traditional predictive met...
Machine Learning Algorithms for Prediction of Ambulation and Wheelchair Transfer Ability in Spina Bifida.
Archives of physical medicine and rehabilitation
Dec 2, 2024
OBJECTIVE: To determine which statistical techniques enhance our ability to predict ambulation and transfer ability in people with spina bifida (SB).
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