AIMC Topic: Child

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Spatial statistical machine learning models to assess the relationship between development vulnerabilities and educational factors in children in Queensland, Australia.

BMC public health
BACKGROUND: The health and development of children during their first year of full time school is known to impact their social, emotional, and academic capabilities throughout and beyond early education. Physical health, motor development, social and...

Effectiveness of cone-beam computed tomography-generated cephalograms using artificial intelligence cephalometric analysis.

Scientific reports
Lateral cephalograms and related analysis constitute representative methods for orthodontic treatment. However, since conventional cephalometric radiographs display a three-dimensional structure on a two-dimensional plane, inaccuracies may be produce...

The effect of an interactive robot on children's post-operative anxiety, mobilization, and parents' satisfaction; randomized controlled study.

Journal of pediatric nursing
PURPOSE: To evaluate the effect of an interactive robot on Turkish children's post-operative anxiety, mobilization, and parents' satisfaction related to post-operative care.

An Introduction to Artificial Intelligence in Developmental and Behavioral Pediatrics.

Journal of developmental and behavioral pediatrics : JDBP
Technological breakthroughs, together with the rapid growth of medical information and improved data connectivity, are creating dramatic shifts in the health care landscape, including the field of developmental and behavioral pediatrics. While medica...

Pediatric Automatic Sleep Staging: A Comparative Study of State-of-the-Art Deep Learning Methods.

IEEE transactions on bio-medical engineering
BACKGROUND: Despite the tremendous prog- ress recently made towards automatic sleep staging in adults, it is currently unknown if the most advanced algorithms generalize to the pediatric population, which displays distinctive characteristics in overn...

The use of machine learning and artificial intelligence within pediatric critical care.

Pediatric research
The field of pediatric critical care has been hampered in the era of precision medicine by our inability to accurately define and subclassify disease phenotypes. This has been caused by heterogeneity across age groups that further challenges the abil...

Multi-Scale Deep Learning of Clinically Acquired Multi-Modal MRI Improves the Localization of Seizure Onset Zone in Children With Drug-Resistant Epilepsy.

IEEE journal of biomedical and health informatics
The present study investigates the effectiveness of a deep learning neural network for non-invasively localizing the seizure onset zone (SOZ) using multi-modal MRI data that are clinically acquired from children with drug-resistant epilepsy. A cortic...

Effect of AI-assisted software on inter- and intra-observer variability for the X-ray bone age assessment of preschool children.

BMC pediatrics
BACKGROUND: With the rapid development of deep learning algorithms and the rapid improvement of computer hardware in the past few years, AI-assisted diagnosis software for bone age has achieved good diagnostic performance. The purpose of this study w...

A novel soft robotic pediatric in vitro swallowing device to gain insights into the swallowability of mini-tablets.

International journal of pharmaceutics
Soft robotics could help providing a better understanding of the mechanisms underpinning the swallowability of solid oral dosage forms (SODF), especially by vulnerable populations such as the elderly or children. In this study a novel soft robotic in...