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Risk Assessment for Parents Who Suspect Their Child Has Autism Spectrum Disorder: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: Parents are likely to seek Web-based communities to verify their suspicions of autism spectrum disorder markers in their child. Automated tools support human decisions in many domains and could therefore potentially support concerned pare...

Using the MEDiPORT humanoid robot to reduce procedural pain and distress in children with cancer: A pilot randomized controlled trial.

Pediatric blood & cancer
BACKGROUND: Subcutaneous port needle insertions are painful and distressing for children with cancer. The interactive MEDiPORT robot has been programmed to implement psychological strategies to decrease pain and distress during this procedure. This s...

A neural network analysis of Lifeways cross-generation imputed data.

BMC research notes
OBJECTIVES: Neural networks are a powerful statistical tool that use nonlinear regression type models to obtain predictions. Their use in the Lifeways cross-generation study that examined body mass index (BMI) of children, among other measures, is ex...

Relative importance of symptoms, cognition, and other multilevel variables for psychiatric disease classifications by machine learning.

Psychiatry research
This study used machine-learning algorithms to make unbiased estimates of the relative importance of various multilevel data for classifying cases with schizophrenia (n = 60), schizoaffective disorder (n = 19), bipolar disorder (n = 20), unipolar dep...

Child and parent perceptions of acceptability and therapeutic value of a socially assistive robot used during pediatric rehabilitation.

Disability and rehabilitation
Socially assistive robots are emerging as a method of supporting the rehabilitation of children with physical disabilities. To date there has been no in-depth analysis of parent and child perspectives regarding the use of socially assistive robots f...

A data driven methodology for social science research with left-behind children as a case study.

PloS one
For decades, traditional correlation analysis and regression models have been used in social science research. However, the development of machine learning algorithms makes it possible to apply machine learning techniques for social science research ...

Adherence and acceptability of a robot-assisted Pivotal Response Treatment protocol for children with autism spectrum disorder.

Scientific reports
The aim of this study is to present a robot-assisted therapy protocol for children with ASD based on the current state-of-the-art in both ASD intervention research and robotics research, and critically evaluate its adherence and acceptability based o...

Using social robot PLEO to enhance the well-being of hospitalised children.

Journal of child health care : for professionals working with children in the hospital and community
Hospitalisation is stressful for children. Play material is often offered for distraction and comfort. We explored how contact with social robot PLEO could positively affect a child's well-being. To this end, we performed a multiple case study on the...

Artificial intelligence as an analytic approximation to evaluate associations between parental feeding behaviours and excess weight in Colombian preschoolers.

The British journal of nutrition
Parental practices can affect children's weight and BMI and may even be related to a high prevalence of obesity. Therefore, the aim of this study was to evaluate the relationship between parents' practices related to feeding their children and excess...

Acceptance of patients towards task-autonomous robotic cochlear implantation: An exploratory study.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Recently, task-autonomous image-guided robotic cochlear implantation has been successfully completed in patients. However, no data exist on patients' perspective of this new technology. The aim of this study was to evaluate the acceptance...