AIMC Topic: Infant, Newborn

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Identifying Factors Associated with Neonatal Mortality in Sub-Saharan Africa using Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This study aimed at identifying the factors associated with neonatal mortality. We analyzed the Demographic and Health Survey (DHS) datasets from 10 Sub-Saharan countries. For each survey, we trained machine learning models to identify women who had ...

Age-group determination of living individuals using first molar images based on artificial intelligence.

Scientific reports
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...

Automatic segmentation of ventricular volume by 3D ultrasonography in post haemorrhagic ventricular dilatation among preterm infants.

Scientific reports
To train, evaluate, and validate the application of a deep learning framework in three-dimensional ultrasound (3D US) for the automatic segmentation of ventricular volume in preterm infants with post haemorrhagic ventricular dilatation (PHVD). We tra...

The Potential and the Limitations of Esophageal Robotic Surgery in Children.

European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie
INTRODUCTION:  There have been numerous reports of robotic pediatric surgery in the literature, particularly regarding urological procedures for school-aged children. Thoracic procedures appear to be less common, despite the fact that encouraging res...

Deep Learning for Classification of Pediatric Otitis Media.

The Laryngoscope
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
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...

Deep Learning Model for Accurate Automatic Determination of Phakic Status in Pediatric and Adult Ultrasound Biomicroscopy Images.

Translational vision science & technology
PURPOSE: Ultrasound biomicroscopy (UBM) is a noninvasive method for assessing anterior segment anatomy. Previous studies were prone to intergrader variability, lacked assessment of the lens-iris diaphragm, and excluded pediatric subjects. Lens status...

Machine Learning for Child and Adolescent Health: A Systematic Review.

Pediatrics
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.

A new deep learning approach integrated with clinical data for the dermoscopic differentiation of early melanomas from atypical nevi.

Journal of dermatological science
BACKGROUND: Timely recognition of malignant melanoma (MM) is challenging for dermatologists worldwide and represents the main determinant for mortality. Dermoscopic examination is influenced by dermatologists' experience and fails to achieve adequate...

Artificial intelligence for automatic cerebral ventricle segmentation and volume calculation: a clinical tool for the evaluation of pediatric hydrocephalus.

Journal of neurosurgery. Pediatrics
OBJECTIVE: Imaging evaluation of the cerebral ventricles is important for clinical decision-making in pediatric hydrocephalus. Although quantitative measurements of ventricular size, over time, can facilitate objective comparison, automated tools for...