AIMC Topic: Child

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Artificial Intelligence for the Objective Evaluation of Acne Investigator Global Assessment.

Journal of drugs in dermatology : JDD
INTRODUCTION: The evaluation of Acne using ordinal scales reflects the clinical perception of severity but has shown low reproducibility both intra- and inter-rater. In this study, we investigated if Artificial Intelligence trained on images of Acne ...

Use of Machine Learning to Determine Deviance in Neuroanatomical Maturity Associated With Future Psychosis in Youths at Clinically High Risk.

JAMA psychiatry
IMPORTANCE: Altered neurodevelopmental trajectories are thought to reflect heterogeneity in the pathophysiologic characteristics of schizophrenia, but whether neural indicators of these trajectories are associated with future psychosis is unclear.

Predicting Language Difficulties in Middle Childhood From Early Developmental Milestones: A Comparison of Traditional Regression and Machine Learning Techniques.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: The current study aimed to compare traditional logistic regression models with machine learning algorithms to investigate the predictive ability of (a) communication performance at 3 years old on language outcomes at 10 years old and (b) bro...

MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling.

Journal of digital imaging
Bone age assessment (BAA) is a commonly performed diagnostic study in pediatric radiology to assess skeletal maturity. The most commonly utilized method for assessment of BAA is the Greulich and Pyle method (Pediatr Radiol 46.9:1269-1274, 2016; Arch ...

Automated Assessment of Bone Age Using Deep Learning and Gaussian Process Regression.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Bone age is an essential measure of skeletal maturity in children with growth disorders. It is typically assessed by a trained physician using radiographs of the hand and a reference model. However, it has been described that the reference models lea...

Striking the Right Balance-Applying Machine Learning to Pediatric Critical Care Data.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies

Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization.

Medical image analysis
fMRI data decomposition techniques have advanced significantly from shallow models such as Independent Component Analysis (ICA) and Sparse Coding and Dictionary Learning (SCDL) to deep learning models such Deep Belief Networks (DBN) and Convolutional...

Arash: A social robot buddy to support children with cancer in a hospital environment.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
This article presents the thorough design procedure, specifications, and performance of a mobile social robot friend Arash for educational and therapeutic involvement of children with cancer based on their interests and needs. Our research focuses on...

A Sibling-Mediated Intervention for Children with Autism Spectrum Disorder: Using the Natural Language Paradigm (NLP).

Journal of autism and developmental disorders
We taught three typically developing siblings to occasion speech by implementing the Natural Language Paradigm (NLP) with their brothers with autism spectrum disorder (ASD). A non-concurrent multiple baseline design across children with ASD and sibli...

[Preliminary study of robot-assisted ankle rehabilitation for children with cerebral palsy].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences
OBJECTIVE: To propose a kind of robotic ankle-foot rehabilitation system for children with cerebral palsy and to preliminarily verify its feasibility in clinical application.