Journal of clinical research in pediatric endocrinology
33099993
Bone age is one of biological indicators of maturity used in clinical practice and it is a very important parameter of a child’s assessment, especially in paediatric endocrinology. The most widely used method of bone age assessment is by performing a...
In recent years, several studies have demonstrated that machine learning and deep learning systems can be very useful to accurately predict brain age. In this work, we propose a novel approach based on complex networks using 1016 T1-weighted MRI brai...
Adult cognitive neuroscience has guided the study of human brain development by identifying regions associated with cognitive functions at maturity. The activity, connectivity, and structure of a region can be compared across ages to characterize the...
The past decade has evinced a boom of computer-based approaches to aid movement assessment in early infancy. Increasing interests have been dedicated to develop AI driven approaches to complement the classic Prechtl general movements assessment (GMA)...
BACKGROUND: Children's motor development is a crucial tool for assessing developmental levels, identifying developmental disorders early, and taking appropriate action. Although the Korean Developmental Screening Test for Infants and Children (K-DST)...
In the target article, Clark and Fischer argue that little is known about children's perceptions of social robots. By reviewing the existing literature we demonstrate that infants and young children interact with robots in the same ways they do with ...
Clark and Fischer propose that people interpret social robots not as social agents, but as interactive depictions. Drawing on research focusing on how children selectively learn from social others, we argue that children do not view social robots as ...
The American journal of occupational therapy : official publication of the American Occupational Therapy Association
37824724
IMPORTANCE: Performance of coloring, origami, and copying activities reflects children's visual-motor integration (VMI), but the levels of association remain unclear.
BACKGROUND: There are no early, accurate, scalable methods for identifying infants at high risk of poor cognitive outcomes in childhood. We aim to develop an explainable predictive model, using machine learning and population-based cohort data, for t...
IEEE journal of biomedical and health informatics
37053059
OBJECTIVE: Cognition is an essential human function, and its development in infancy is crucial. Traditionally, pediatricians used clinical observation or medical imaging to assess infants' current cognitive development (CD) status. The object of pedi...