Using a computer algorithm, scientists at Uppsala University have identified a promising new treatment for neuroblastoma.
Ensembles created using models submitted to the RSNA Pediatric Bone Age Machine Learning Challenge convincingly outperformed single-model prediction of bone age.
A new type of ultrasound transducer should soon be delivering a fast and reliable diagnosis of infection of the middle ear.
Using a game, researchers are rehabilitating children who suffer from cognitive impairment after surviving life-threatening diseases such as malaria and HIV.
Interacting with a robotic teddy bear invented at MIT boosted young patients’ positive emotions, engagement, and activity level.
Children with autism improved measurably on a test of socialization and learning when their therapy included an at-home intervention with Google Glass.
Researchers have designed a therapeutic robot that simulates human skin-to-skin contact, helping reduce pain for babies in the neonatal intensive care unit.
Researchers are working on a smartphone app that could help diagnose autism in minutes – and provide ongoing therapy as well, all with fewer visits to specialized clinics.
A machine learning algorithm was able to sort children with arthritis into distinct categories based on their patterns of inflamed joints in the body in a way that was also predictive of disease outcome.
Researchers have developed a wearable, disposable respiration monitor that provides high-fidelity readings on a continuous basis.
Researchers evaluated a digital medicine tool designed as an investigational treatment for children with autism spectrum disorder (ASD) and co-occurring ADHD.
Researchers use the analogy of raindrops on the sidewalk to explain their new method to identify genetic variations that cause severe pediatric diseases.
Biomedical engineers have designed 3D-printed tracheal splints for pediatric patients. These were used to assist the breathing of an infant battling a life-threatening airway obstruction.