AIMC Topic: Child

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Numerosity discrimination in deep neural networks: Initial competence, developmental refinement and experience statistics.

Developmental science
Both humans and non-human animals exhibit sensitivity to the approximate number of items in a visual array, as indexed by their performance in numerosity discrimination tasks, and even neonates can detect changes in numerosity. These findings are oft...

Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project.

BMJ open
INTRODUCTION: Around 70% to 80% of the 19 million visually disabled children in the world are due to a preventable or curable disease, if detected early enough. Vision screening in childhood is an evidence-based and cost-effective way to detect visua...

Plus Disease in Retinopathy of Prematurity: Convolutional Neural Network Performance Using a Combined Neural Network and Feature Extraction Approach.

Translational vision science & technology
PURPOSE: Retinopathy of prematurity (ROP), a leading cause of childhood blindness, is diagnosed by clinical ophthalmoscopic examinations or reading retinal images. Plus disease, defined as abnormal tortuosity and dilation of the posterior retinal blo...

Effects of interactive robot-enhanced hand rehabilitation in treatment of paediatric hand-burns: A randomized, controlled trial with 3-months follow-up.

Burns : journal of the International Society for Burn Injuries
PURPOSE: To evaluate the effectiveness of the robotic-assisted exercise with virtual gaming on total active range of motion (ROM) of the digits, hand grip strength (HGS), and hand function in children with hand burns.

Artificial Intelligence in Retinopathy of Prematurity Diagnosis.

Translational vision science & technology
Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide. The diagnosis of ROP is subclassified by zone, stage, and plus disease, with each area demonstrating significant intra- and interexpert subjectivity and disagreemen...

A review of recent research in social robotics.

Current opinion in psychology
Research in social robotics has a different emphasis from research in robotics for factory, military, hospital, home (vacuuming), aerial (drone), space, and undersea applications. A social robot is one whose purpose is to serve a person in a caring i...

Feature rearrangement based deep learning system for predicting heart failure mortality.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Heart Failure is a clinical syndrome commonly caused by any structural or functional impairment. Fast and accurate mortality prediction for Heart Failure is essential to improve the health care of patients and prevent them f...

Somatosensory evoked fields predict response to vagus nerve stimulation.

NeuroImage. Clinical
There is an unmet need to develop robust predictive algorithms to preoperatively identify pediatric epilepsy patients who will respond to vagus nerve stimulation (VNS). Given the similarity in the neural circuitry between vagus and median nerve affer...

Deep Neural Networks for Chronological Age Estimation From OPG Images.

IEEE transactions on medical imaging
Chronological age estimation is crucial labour in many clinical procedures, where the teeth have proven to be one of the best estimators. Although some methods to estimate the age from tooth measurements in orthopantomogram (OPG) images have been dev...