AIMC Topic: Child

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Artificial intelligence-powered smart vision glasses for the visually impaired.

Indian journal of ophthalmology
PURPOSE: In India, 4.80 million people are blind, and 4.69 million have severe visual impairment. Globally, the digital era and the advent of artificial intelligence devices offer solutions for daily challenges faced by the visually impaired, but the...

Digital Pathology and Artificial Intelligence in Pediatric Pathology.

Surgical pathology clinics
Applications of artificial intelligence (AI) and machine learning (ML) are rapidly developing to support the diagnosis and classification of pathology specimens. These tools rely on digitization of pathology glass slides as whole slide images, allowi...

Diagnostic Stewardship of Blood Cultures in the Pediatric ICU Using Machine Learning.

Hospital pediatrics
OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottles. Rates of blood stream infection (BSI) among critically ill children are low. We sought to design a machine learning (ML) model able to identify ch...

Exploring the link between grandmaternal air pollution exposure and Grandchild's ASD risk: A multigenerational population-based study in California.

Environment international
BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with increasing prevalence. While genetics play a strong causal role, among environmental factors, air pollution (AP) exposure in pregnancy and infancy has been strongly endo...

Use of an Untrained Large Language Model for Antibiotic Prescription in Pediatric Infectious Diseases at Primary Care Settings: A Study From the Italian Society for Pediatric Infectious Diseases.

The Pediatric infectious disease journal
The development of artificial intelligence systems is revolutionizing many fields of medicine, but specific studies are still missing in pediatrics. In our study, we showed that an untrained free-to-use large language model provided reliable response...

Advances in pharmacotherapy of juvenile idiopathic arthritis.

Expert opinion on pharmacotherapy
INTRODUCTION: Juvenile Idiopathic Arthritis (JIA) is the most common chronic rheumatic disease in childhood. More therapeutic options are available for the treatment of JIA with more children achieving minimal active disease or inactive disease statu...

Machine Learning for Predicting Waitlist Mortality in Pediatric Heart Transplantation.

Pediatric transplantation
BACKGROUND: Waitlist mortality remains a critical issue for pediatric heart transplant (HTx) candidates, particularly for candidates with congenital heart disease. Listing center organ offer acceptance practices have been identified as a factor influ...

Pediatric chest X-ray diagnosis using neuromorphic models.

Computers in biology and medicine
This research presents an innovative neuromorphic method utilizing Spiking Neural Networks (SNNs) to analyze pediatric chest X-rays (PediCXR) to identify prevalent thoracic illnesses. We incorporate spiking-based machine learning models such as Spiki...

Wrist and elbow fracture detection and segmentation by artificial intelligence using point-of-care ultrasound.

Journal of ultrasound
PURPOSE: Distal radius (wrist) and supracondylar (elbow) fractures are common in children presenting to Pediatric Emergency Departments (EDs). These fractures are treated conservatively or surgically depending on deformity severity. Radiographs are t...

Artificial intelligence-supported occupational therapy program on handwriting skills in children at risk for developmental coordination disorder: Randomized controlled trial.

Research in developmental disabilities
AIM: This study investigates the impact of an AI-supported occupational therapy program, developed using the Model of Human Occupation (MOHO), on handwriting skills in children at risk for Developmental Coordination Disorder (DCD).