AIMC Topic: Child

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Artificial Intelligence Algorithm Improves Radiologist Performance in Skeletal Age Assessment: A Prospective Multicenter Randomized Controlled Trial.

Radiology
Background Previous studies suggest that use of artificial intelligence (AI) algorithms as diagnostic aids may improve the quality of skeletal age assessment, though these studies lack evidence from clinical practice. Purpose To compare the accuracy ...

Robot-assisted laparoscopic urologic surgery in infants weighing ≤10 kg: A weight stratified analysis.

Journal of pediatric urology
INTRODUCTION: Robot-assisted laparoscopic (RAL) urologic surgery is widely used in pediatric patients, though less commonly in infants. There are small series demonstrating safety and efficacy in infants, however, stratification by infant size has ra...

Identification of Sex and Age from Macular Optical Coherence Tomography and Feature Analysis Using Deep Learning.

American journal of ophthalmology
PURPOSE: To develop deep learning models for identification of sex and age from macular optical coherence tomography (OCT) and to analyze the features for differentiation of sex and age.

Combining multi-site magnetic resonance imaging with machine learning predicts survival in pediatric brain tumors.

Scientific reports
Brain tumors represent the highest cause of mortality in the pediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging. Survival biomarkers are challenging to identify due to the relatively low numbers of indiv...

Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach.

Nature communications
Assisted reproductive technologies (ART) are increasingly used, however little is known about the long-term health of ART-conceived offspring. Weak selection of comparison groups and poorly characterized mechanisms impede current understanding. In a ...

Deep learning methods for automatic segmentation of lower leg muscles and bones from MRI scans of children with and without cerebral palsy.

NMR in biomedicine
Cerebral palsy is a neurological condition that is known to affect muscle growth. Detailed investigations of muscle growth require segmentation of muscles from MRI scans, which is typically done manually. In this study, we evaluated the performance o...

RGB-D scene analysis in the NICU.

Computers in biology and medicine
Continuity of care is achieved in the neonatal intensive care unit (NICU) through careful documentation of all events of clinical significance, including clinical interventions and routine care events (e.g., feeding, diaper change, weighing, etc.). A...

A Deep Learning Algorithm for Objective Assessment of Hypernasality in Children With Cleft Palate.

IEEE transactions on bio-medical engineering
OBJECTIVES: Evaluation of hypernasality requires extensive perceptual training by clinicians and extending this training on a large scale internationally is untenable; this compounds the health disparities that already exist among children with cleft...

A Machine Learning Model for Evaluating Imported Disease Screening Strategies in Immigrant Populations.

The American journal of tropical medicine and hygiene
Given the high prevalence of imported diseases in immigrant populations, it has postulated the need to establish screening programs that allow their early diagnosis and treatment. We present a mathematical model based on machine learning methodologie...

Robot-Assisted Laparoscopic Management of Bladder/Prostate Rhabdomyosarcoma in Children: Initial Series and 1-Year Outcomes.

Journal of endourology
To present our preliminary experiences of robot-assisted laparoscopic radical or partial cystectomy for bladder/prostate rhabdomyosarcoma (B/P RMS) in children. A retrospective study was conducted with children who underwent robot-assisted laparosc...