AIMC Topic: Child

Clear Filters Showing 2561 to 2570 of 3433 articles

Can Dogs Assist Children with Severe Autism Spectrum Disorder in Complying with Challenging Demands? An Exploratory Experiment with a Live and a Robotic Dog.

Journal of alternative and complementary medicine (New York, N.Y.)
OBJECTIVES: Prompted by the need to find effective ways to enhance compliance in children with autism spectrum disorder (ASD), and building on the increasing interest in dog-assisted interventions for this population, this study provides an explorato...

Estimating a person's age from walking over a sensor floor.

Computers in biology and medicine
Ageing has an effect on many parameters of the physical condition, and one of them is the way a person walks. This property, the gait pattern, can unintrusively be observed by letting people walk over a sensor floor. The electric capacitance sensors ...

Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs.

Radiology
Purpose To compare the performance of a deep-learning bone age assessment model based on hand radiographs with that of expert radiologists and that of existing automated models. Materials and Methods The institutional review board approved the study....

The diagnostic value of hepcidin to predict the presence and severity of appendicitis in children.

The Journal of surgical research
BACKGROUND: The aim of this study was to determine the diagnostic capacity of hepcidin in pediatric acute appendicitis and its accuracy as a predictor of the severity of appendicitis.

Quantitative surface analysis of combined MRI and PET enhances detection of focal cortical dysplasias.

NeuroImage
OBJECTIVE: Focal cortical dysplasias (FCDs) often cause pharmacoresistant epilepsy, and surgical resection can lead to seizure-freedom. Magnetic resonance imaging (MRI) and positron emission tomography (PET) play complementary roles in FCD identifica...

MRI features predict p53 status in lower-grade gliomas via a machine-learning approach.

NeuroImage. Clinical
BACKGROUND: P53 mutation status is a pivotal biomarker for gliomas. Here, we developed a machine-learning model to predict p53 status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images.

Whole brain white matter connectivity analysis using machine learning: An application to autism.

NeuroImage
In this paper, we propose an automated white matter connectivity analysis method for machine learning classification and characterization of white matter abnormality via identification of discriminative fiber tracts. The proposed method uses diffusio...

Automatic recognition of therapy progress among children with autism.

Scientific reports
The article presents a research study on recognizing therapy progress among children with autism spectrum disorder. The progress is recognized on the basis of behavioural data gathered via five specially designed tablet games. Over 180 distinct param...

Identification of immune signatures predictive of clinical protection from malaria.

PLoS computational biology
Antibodies are thought to play an essential role in naturally acquired immunity to malaria. Prospective cohort studies have frequently shown how continuous exposure to the malaria parasite Plasmodium falciparum cause an accumulation of specific respo...