AIMC Topic: Infant

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eDeeplepsy: An artificial neural framework to reveal different brain states in children with epileptic spasms.

Epilepsy & behavior : E&B
OBJECTIVE: Despite advances, analysis and interpretation of EEG still essentially rely on visual inspection by a super-specialized physician. Considering the vast amount of data that composes the EEG, much of the detail inevitably escapes ordinary hu...

Optimization of Ganciclovir and Valganciclovir Starting Dose in Children by Machine Learning.

Clinical pharmacokinetics
BACKGROUND AND OBJECTIVES: Ganciclovir (GCV) and valganciclovir (VGCV) show large interindividual pharmacokinetic variability, particularly in children. The objectives of this study were (1) to develop machine learning (ML) algorithms trained on simu...

A Longitudinal Analysis of Pre- and Post-Operative Dysmorphology in Metopic Craniosynostosis.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
OBJECTIVE: The purpose of this study is to objectively quantify the degree of overcorrection in our current practice and to evaluate longitudinal morphological changes using CranioRate, a novel machine learning skull morphology assessment tool.  Desi...

A survey of patient acceptability of the use of artificial intelligence in the diagnosis of paediatric fractures: an observational study.

Annals of the Royal College of Surgeons of England
INTRODUCTION: This study aimed to assess carer attitudes towards the use of artificial intelligence (AI) in management of fractures in paediatric patients. As fracture clinic services come under increasing pressure, innovative solutions are needed to...

The infant health effects of doulas: Leveraging big data and machine learning to inform cost-effective targeting.

Health economics
Doula services represent an underutilized maternal and child health intervention with the potential to improve outcomes through the provision of physical, emotional, and informational support. However, there is limited evidence of the infant health e...

Intelligence Sparse Sensor Network for Automatic Early Evaluation of General Movements in Infants.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
General movements (GMs) have been widely used for the early clinical evaluation of infant brain development, allowing immediate evaluation of potential development disorders and timely rehabilitation. The infants' general movements can be captured di...

Use of a machine learning algorithm with a focus on spinopelvic parameters to predict development of symptomatic tethered cord after initial untethering surgery.

Journal of neurosurgery. Pediatrics
OBJECTIVE: Among patients with a history of prior lipomyelomeningocele repair, an association between increased lumbosacral angle (LSA) and cord retethering has been described. The authors sought to build a predictive algorithm to determine which com...

Biomimetic Deep Learning Networks With Applications to Epileptic Spasms and Seizure Prediction.

IEEE transactions on bio-medical engineering
OBJECTIVE: In this study, we present a novel biomimetic deep learning network for epileptic spasms and seizure prediction and compare its performance with state-of-the-art conventional machine learning models.

Information fusion for infant age estimation from deciduous teeth using machine learning.

American journal of biological anthropology
OBJECTIVES: Over the past few years, several methods have been proposed to improve the accuracy of age estimation in infants with a focus on dental development as a reliable marker. However, traditional approaches have limitations in efficiently comb...