AI Medical Compendium Topic:
Child

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Deep learning classification of reading disability with regional brain volume features.

NeuroImage
Developmental reading disability is a prevalent and often enduring problem with varied mechanisms that contribute to its phenotypic heterogeneity. This mechanistic and phenotypic variation, as well as relatively modest sample sizes, may have limited ...

A framework for prediction of personalized pediatric nuclear medical dosimetry based on machine learning and Monte Carlo techniques.

Physics in medicine and biology
A methodology is introduced for the development of an internal dosimetry prediction toolkit for nuclear medical pediatric applications. The proposed study exploits Artificial Intelligence techniques using Monte Carlo simulations as ground truth for a...

Pediatric Deterioration Detection Using Machine Learning.

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

And then there was one … incision. First single-port pediatric robotic case series.

Journal of pediatric urology
BACKGROUND: In the past two decades, technology has advanced to augment an already minimally-invasive approach in laparoscopic surgery. Robotic-assisted laparoscopic platforms have now evolved to its 4th-generation product: a single-port system, firs...

Acquisition time reduction in pediatric Tc-DMSA planar imaging using deep learning.

Journal of applied clinical medical physics
PURPOSE: Given the potential risk of motion artifacts, acquisition time reduction is desirable in pediatric Tc-dimercaptosuccinic acid (DMSA) scintigraphy. The aim of this study was to evaluate the performance of predicted full-acquisition-time imag...

Of children and social robots.

The Behavioral and brain sciences
In the target article, Clark and Fischer argue that little is known about children's perceptions of social robots. By reviewing the existing literature we demonstrate that infants and young children interact with robots in the same ways they do with ...

Social robots as social learning partners: Exploring children's early understanding and learning from social robots.

The Behavioral and brain sciences
Clark and Fischer propose that people interpret social robots not as social agents, but as interactive depictions. Drawing on research focusing on how children selectively learn from social others, we argue that children do not view social robots as ...

Children's interactions with virtual assistants: Moving beyond depictions of social agents.

The Behavioral and brain sciences
Clark and Fischer argue that people see social robots as depictions of social agents. However, people's interactions with virtual assistants may change their beliefs about social robots. Children and adults with exposure to virtual assistants may vie...

Myopia prediction for children and adolescents via time-aware deep learning.

Scientific reports
This is a retrospective analysis. Quantitative prediction of the children's and adolescents' spherical equivalent based on their variable-length historical vision records. From October 2019 to March 2022, we examined uncorrected visual acuity, sphere...