AIMC Topic: Child, Preschool

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Participation and Enjoyment in Play with a Robot between Children with Cerebral Palsy who use AAC and their Peers.

Augmentative and alternative communication (Baltimore, Md. : 1985)
This study explores children with complex communication needs, their peers and adult support persons in play with the talking and moving robot LekBot. Two triads were filmed playing with LekBot at pre-school. LekBot was developed to facilitate indepe...

Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

Burns : journal of the International Society for Burn Injuries
INTRODUCTION: Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational faci...

Multiscale Modeling of Gene-Behavior Associations in an Artificial Neural Network Model of Cognitive Development.

Cognitive science
In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively...

Robot-assisted gait training might be beneficial for more severely affected children with cerebral palsy.

Developmental neurorehabilitation
PURPOSE: Robot-assisted gait training (RAGT) can complement conventional therapies in children with cerebral palsy. We investigated changes in walking-related outcomes between children with different Gross Motor Function Classification System (GMFCS)...

Relative Attribute SVM+ Learning for Age Estimation.

IEEE transactions on cybernetics
When estimating age, human experts can provide privileged information that encodes the facial attributes of aging, such as smoothness, face shape, face acne, wrinkles, and bags under-eyes. In automatic age estimation, privileged information is unavai...

Predictive modeling in pediatric traumatic brain injury using machine learning.

BMC medical research methodology
BACKGROUND: Pediatric traumatic brain injury (TBI) constitutes a significant burden and diagnostic challenge in the emergency department (ED). While large North American research networks have derived clinical prediction rules for the head injured ch...

Abstract computation in schizophrenia detection through artificial neural network based systems.

TheScientificWorldJournal
Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fr...

Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning.

Translational psychiatry
Although the prevalence of autism spectrum disorder (ASD) has risen sharply in the last few years reaching 1 in 68, the average age of diagnosis in the United States remains close to 4--well past the developmental window when early intervention has t...

Considering the effects of gender in child-robot interaction studies: comment on Srinivasan, et Al. (2013).

Perceptual and motor skills
Using a pretest-posttest design, Srinivasan, et al. (2013 ) found that a period of interaction between children and an Isobot humanoid robot improved performance on standardized measures of imitation, planning, and execution of motor behaviors. The a...