Pediatrics

Multi-media biomarkers: Integrating information to improve lead exposure assessment.

Exposure assessment traditionally relies on biomarkers that measure chemical concentrations in individual biological media (i.e., blood, urine, etc.). However, chemicals distribute unevenly among different biological media; thus, each medium provides incomplete information about body burden. We propose that machine learning and statistical approaches can create integrated exposure estimates from m...

A Machine Learning Approach to Growth Direction Finding for Automated Planting of Bulbous Plants.

In agricultural robotics, a unique challenge exists in the automated planting of bulbous plants: the estimation of the bulb's growth direction. To date, no existing work addresses this challenge. Therefore, we propose the first robotic vision framework for the estimation of a plant bulb's growth direction. The framework takes as input three x-ray images of the bulb and extracts shape, edge, and te...

Promotes Stable Polymicrobial Biofilms With the Major Otopathogens.

Otitis media (OM) is a prevalent pediatric infection characterized by painful inflammation of the middle ear. The Gram-negative diplococcus is a comm...

Digging Deeper to Save the Old Anti-tuberculosis Target: D-Alanine-D-Alanine Ligase With a Novel Inhibitor, IMB-0283.

The emergence of drug-resistant (Mtb) has hampered treatments for tuberculosis, which consequently now require novel agents to overcome such drug res...

Prediction of Myopia in Adolescents through Machine Learning Methods.

According to literature, myopia has become the second most common eye disease in China, and the incidence of myopia is increasing year by year, and sh...

Current Status of Pediatric Robot-Assisted Surgery in Italy: Epidemiologic National Survey and Future Directions.

Pediatric robot-assisted surgery (RAS) is gaining increasing acceptance. We aimed to assess the diffusion of pediatric RAS in Italy, the training per...

How much are we exposed to alcohol in electronic media? Development of the Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA).

BACKGROUND: Evidence demonstrates that seeing alcoholic beverages in electronic media increases alcohol initiation and frequent and excessive drinking...

Enablers and barriers to the implementation of socially assistive humanoid robots in health and social care: a systematic review.

OBJECTIVES: Socially assistive humanoid robots are considered a promising technology to tackle the challenges in health and social care posed by the g...

A practical model for the identification of congenital cataracts using machine learning.

BACKGROUND: Approximately 1 in 33 newborns is affected by congenital anomalies worldwide. We aimed to develop a practical model for identifying infant...

Artificial intelligence, machine learning and the pediatric airway.

Artificial intelligence and machine learning are rapidly expanding fields with increasing relevance in anesthesia and, in particular, airway managemen...

A Multidimensional Neural Maturation Index Reveals Reproducible Developmental Patterns in Children and Adolescents.

Adolescence is a time of extensive neural restructuring, leaving one susceptible to atypical development. Although neural maturation in humans can be ...

Microplastics but not natural particles induce multigenerational effects in Daphnia magna.

Several studies have investigated the effects of nano- and microplastics on daphnids as key freshwater species. However, while information is abundant...

Reinforcement Learning for Bioretrosynthesis.

Metabolic engineering aims to produce chemicals of interest from living organisms, to advance toward greener chemistry. Despite efforts, the research ...

Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department.

OBJECTIVE: To examine the association between the medical imaging utilization and information related to patients' socioeconomic, demographic and clin...

Motivational interviewing and culture for urban Native American youth (MICUNAY): A randomized controlled trial.

To date, few programs that integrate traditional practices with evidence-based practices have been developed, implemented, and evaluated with urban Am...

Predicting the serum digoxin concentrations of infants in the neonatal intensive care unit through an artificial neural network.

BACKGROUND: Given its narrow therapeutic range, digoxin's pharmacokinetic parameters in infants are difficult to predict due to variation in birth wei...

Deep Convolutional Neural Network-Based Automatic Classification of Neonatal Hip Ultrasound Images: A Novel Data Augmentation Approach with Speckle Noise Reduction.

Neonatal hip ultrasound imaging has been widely used for a few decades in the diagnosis of developmental dysplasia of the hip (DDH). Graf's method of ...

Preterm Infants' Pose Estimation With Spatio-Temporal Features.

OBJECTIVE: Preterm infants' limb monitoring in neonatal intensive care units (NICUs) is of primary importance for assessing infants' health status and...

Evaluation of the effect of Lactobacillus sakei strain L115 on Listeria monocytogenes at different conditions of temperature by using predictive interaction models.

In this study, the inhibitory capacity of Lactobacillus sakei strain L115 against Listeria monocytogenes has been assayed at 4, 8, 11, 15 and 20 °C in...

DW-Net: A cascaded convolutional neural network for apical four-chamber view segmentation in fetal echocardiography.

Fetal echocardiography (FE) is a widely used medical examination for early diagnosis of congenital heart disease (CHD). The apical four-chamber view (...