AIMC Topic: Infant
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Age-group determination of living individuals using first molar images based on artificial intelligence.
Scientific reports
Jan 13, 2021
Dental age estimation of living individuals is difficult and challenging, and there is no consensus method in adults with permanent dentition. Thus, we aimed to provide an accurate and robust artificial intelligence (AI)-based diagnostic system for a...
Quantitative evaluation of chronically obstructed kidneys from noncontrast computed tomography based on deep learning.
European journal of radiology
Jan 10, 2021
OBJECTIVE: To quantitatively report renal parenchymal volume (RPV), renal sinus volume (RSV), and renal parenchymal density (RPD) for chronically obstructed kidneys from noncontrast computed tomography (NCCT).
The impact of errors in infant development: Falling like a baby.
Developmental science
Jan 4, 2021
What is the role of errors in infants' acquisition of basic skills such as walking, skills that require immense amounts of practice to become flexible and generative? Do infants change their behaviors based on negative feedback from errors, as sugges...
Deep Learning for Classification of Pediatric Otitis Media.
The Laryngoscope
Dec 28, 2020
OBJECTIVES/HYPOTHESIS: To create a new strategy for monitoring pediatric otitis media (OM), we developed a brief, reliable, and objective method for automated classification using convolutional neural networks (CNNs) with images from otoscope.
Robotic Uses in Pediatric Care: A Comprehensive Review.
Journal of pediatric nursing
Dec 25, 2020
PROBLEM: Advances in technology have made robotics acceptable in healthcare and medical environments. The aim of this literature review was to examine how the pediatric population can benefit from robotic therapy and assistance that are currently ava...
Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental study.
Neural networks : the official journal of the International Neural Network Society
Dec 23, 2020
Recently, the focus of functional connectivity analysis of human brain has shifted from merely revealing the inter-regional functional correlation over the entire scan duration to capturing the time-varying information of brain networks and character...
Reducing scan time of paediatric Tc-DMSA SPECT via deep learning.
Clinical radiology
Dec 16, 2020
AIM: To investigate the feasibility of reducing the scan time of paediatric technetium 99m (Tc) dimercaptosuccinic acid (DMSA) single-photon-emission computed tomographic (SPECT) using a deep learning (DL) method.
Machine Learning for Child and Adolescent Health: A Systematic Review.
Pediatrics
Dec 15, 2020
CONTEXT: In the last few decades, data acquisition and processing has seen tremendous amount of growth, thus sparking interest in machine learning (ML) within the health care system.
Detection of eye contact with deep neural networks is as accurate as human experts.
Nature communications
Dec 14, 2020
Eye contact is among the most primary means of social communication used by humans. Quantification of eye contact is valuable as a part of the analysis of social roles and communication skills, and for clinical screening. Estimating a subject's looki...
Selecting Children with Vesicoureteral Reflux Who are Most Likely to Benefit from Antibiotic Prophylaxis: Application of Machine Learning to RIVUR.
The Journal of urology
Dec 8, 2020
PURPOSE: Continuous antibiotic prophylaxis reduces the risk of recurrent urinary tract infection by 50% in children with vesicoureteral reflux. However, there may be subgroups in whom continuous antibiotic prophylaxis could be used more selectively. ...
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