AI Medical Compendium Topic:
Child

Clear Filters Showing 891 to 900 of 3011 articles

Machine Learning Differentiation of Autism Spectrum Sub-Classifications.

Journal of autism and developmental disorders
PURPOSE: Disorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges can be mitigated with early identification. However, diagnostic crite...

Clinical Uptake of Pediatric Exoskeletons: Pilot Study Using the Consolidated Framework for Implementation Research.

American journal of physical medicine & rehabilitation
OBJECTIVE: While the design and clinical evidence base of robot-assisted gait training devices has been advancing, few studies investigate user experiences with accessing and using such devices in pediatric rehabilitation. This pilot study aims to fu...

Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project.

Pediatric radiology
This review paper presents the practical development of imaging biomarkers in the scope of the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project, as a n...

Examining the Impact of Assistive Technology on Psychological Health, Family Education, and Curriculum Research in Japan: Insights from Artificial Intelligence.

Journal of autism and developmental disorders
This study aims to analyze the effect of psychological health based on artificial intelligence agent technology on the implementation effect of Japanese family education. By combining mobile agent technology and education thought, the system structur...

Artificial intelligence to identify fractures on pediatric and young adult upper extremity radiographs.

Pediatric radiology
BACKGROUND: Pediatric fractures are challenging to identify given the different response of the pediatric skeleton to injury compared to adults, and most artificial intelligence (AI) fracture detection work has focused on adults.

Evaluation of height prediction models: from traditional methods to artificial intelligence.

Pediatric research
BACKGROUND: Traditional methods for predicting adult height (AHP) rely on manual readings of bone age (BA). However, the incorporation of artificial intelligence has recently improved the accuracy of BA readings and their incorporation into AHP model...

Predicting 'Brainage' in late childhood to adolescence (6-17yrs) using structural MRI, morphometric similarity, and machine learning.

Scientific reports
Brain development is regularly studied using structural MRI. Recently, studies have used a combination of statistical learning and large-scale imaging databases of healthy children to predict an individual's age from structural MRI. This data-driven,...

Cost-effectiveness analysis of robot-assisted laparoscopic surgery for complex pediatric surgical conditions.

Surgical endoscopy
BACKGROUND: Robotics has been used safely and successfully in a variety of adult surgeries and is gradually gaining ground in pediatrics. While the benefits of robotic-assisted surgery in disease treatment are well recognized, its high cost has led t...

Artificial Intelligence in Pediatric Urology.

The Urologic clinics of North America
Application of artificial intelligence (AI) is one of the hottest topics in medicine. Unlike traditional methods that rely heavily on statistical assumptions, machine learning algorithms can identify highly complex patterns from data, allowing robust...