AIMC Topic: Child Development

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Multi-task prediction of infant cognitive scores from longitudinal incomplete neuroimaging data.

NeuroImage
Early postnatal brain undergoes a stunning period of development. Over the past few years, research on dynamic infant brain development has received increased attention, exhibiting how important the early stages of a child's life are in terms of brai...

Creepiness Creeps In: Uncanny Valley Feelings Are Acquired in Childhood.

Child development
The uncanny valley posits that very human-like robots are unsettling, a phenomenon amply demonstrated in adults but unexplored in children. Two hundred forty 3- to 18-year-olds viewed one of two robots (machine-like or very human-like) and rated thei...

Detecting Abnormal Word Utterances in Children With Autism Spectrum Disorders: Machine-Learning-Based Voice Analysis Versus Speech Therapists.

Perceptual and motor skills
Abnormal prosody is often evident in the voice intonations of individuals with autism spectrum disorders. We compared a machine-learning-based voice analysis with human hearing judgments made by 10 speech therapists for classifying children with auti...

Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning.

The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry
OBJECTIVES: One of the major challenges facing psychiatry is how to incorporate biological measures in the classification of mental health disorders. Many of these disorders affect brain development and its connectivity. In this study, we propose a n...

A comparison of the efficacy of weight-shift vs. joystick control of a robotic mobility device by infants ages 5 to 10 months.

Assistive technology : the official journal of RESNA
The onset of crawling in infants contributes to cognitive, perceptual, social, and emotional development. Conversely, infants with motor impairment that delays or prevents autonomous mobility often have associated developmental delays. Evidence sugge...

What do we learn about development from baby robots?

Wiley interdisciplinary reviews. Cognitive science
Understanding infant development is one of the great scientific challenges of contemporary science. In addressing this challenge, robots have proven useful as they allow experimenters to model the developing brain and body and understand the processe...

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...

Electroencephalography estimates brain age in infants with high precision: Leveraging advanced machine learning in healthcare.

NeuroImage
Changes in the pace of neurodevelopment are key indicators of atypical maturation during early life. Unfortunately, reliable prognostic tools rely on assessments of cognitive and behavioral skills that develop towards the second year of life and afte...

A scoping review and quality assessment of machine learning techniques in identifying maternal risk factors during the peripartum phase for adverse child development.

PloS one
Maternal exposure to environmental risk factors (e.g., heavy metal exposure) or mental health problems during the peripartum phase has been shown to lead to negative and lasting impacts on child development and life in adulthood. Given the importance...

Using Artificial Intelligence to Identify the Associations of Children's Performance of Coloring, Origami, and Copying Activities With Visual-Motor Integration.

The American journal of occupational therapy : official publication of the American Occupational Therapy Association
IMPORTANCE: Performance of coloring, origami, and copying activities reflects children's visual-motor integration (VMI), but the levels of association remain unclear.