Pediatrics

Hybrid Artificial Root Foraging Optimizer Based Multilevel Threshold for Image Segmentation.

This paper proposes a new plant-inspired optimization algorithm for multilevel threshold image segmentation, namely, hybrid artificial root foraging optimizer (HARFO), which essentially mimics the iterative root foraging behaviors. In this algorithm the new growth operators of branching, regrowing, and shrinkage are initially designed to optimize continuous space search by combining root-to-root c...

Support vector machine applied to predict the zoonotic potential of E. coli O157 cattle isolates.

Sequence analyses of pathogen genomes facilitate the tracking of disease outbreaks and allow relationships between strains to be reconstructed and virulence factors to be identified. However, these methods are generally used after an outbreak has happened. Here, we show that support vector machine analysis of bovine E. coli O157 isolate sequences can be applied to predict their zoonotic potential,...

The effect of the neural activity on topological properties of growing neural networks.

The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal...

Estimation of umbilical cord blood leptin and insulin based on anthropometric data by means of artificial neural network approach: identifying key maternal and neonatal factors.

BACKGROUND: Leptin and insulin levels are key factors regulating fetal and neonatal energy homeostasis, development and growth. Both biomarkers are us...

Developing an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers.

OBJECTIVE: The objective of this study is to develop an algorithm to accurately identify children with severe early onset childhood obesity (ages 1-5....

Consistent quantitative gene product expression: #1. Automated identification of regenerating bone marrow cell populations using support vector machines.

Identification and quantification of maturing hematopoietic cell populations in flow cytometry data sets is a complex and sometimes irreproducible ste...

Multiclass imbalance learning: Improving classification of pediatric brain tumors from magnetic resonance spectroscopy.

PURPOSE: Classification of pediatric brain tumors from H-magnetic resonance spectroscopy (MRS) can aid diagnosis and management of brain tumors. Howe...

Morbidly Adherent Placenta: Its Management and Maternal and Perinatal Outcome.

OBJECTIVES: The aim of the study was to identify the risk factors predisposing to morbidly adherent placenta and to study the different modes of manag...

In vitro prebiotic effects and quantitative analysis of Bulnesia sarmienti extract.

Prebiotics are used to influence the growth, colonization, survival, and activity of probiotics, and enhance the innate immunity, thus improving the h...

Investigating Approaches to Estimating Covariate Effects in Growth Mixture Modeling: A Simulation Study.

Researchers continue to be interested in efficient, accurate methods of estimating coefficients of covariates in mixture modeling. Including covariate...

Modeling and optimization of Newfoundland shrimp waste hydrolysis for microbial growth using response surface methodology and artificial neural networks.

The hydrolyzed protein derived from seafood waste is regarded as a premium and low-cost nitrogen source for microbial growth. In this study, optimizat...

Real-time multi-channel monitoring of burst-suppression using neural network technology during pediatric status epilepticus treatment.

OBJECTIVE: To develop a real-time monitoring system that has the potential to guide the titration of anesthetic agents in the treatment of pediatric s...

An ensemble method for extracting adverse drug events from social media.

OBJECTIVE: Because adverse drug events (ADEs) are a serious health problem and a leading cause of death, it is of vital importance to identify them co...

Evaluation of knowledge-based reconstruction for magnetic resonance volumetry of the right ventricle after arterial switch operation for dextro-transposition of the great arteries.

Right ventricular (RV) volume and function evaluation is essential in the follow-up of patients after arterial switch operation (ASO) for dextro-trans...

Models of logistic regression analysis, support vector machine, and back-propagation neural network based on serum tumor markers in colorectal cancer diagnosis.

We evaluated the application of three machine learning algorithms, including logistic regression, support vector machine and back-propagation neural n...

Prediction of brain maturity in infants using machine-learning algorithms.

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, se...

Will they participate? Predicting patients' response to clinical trial invitations in a pediatric emergency department.

OBJECTIVE: (1) To develop an automated algorithm to predict a patient's response (ie, if the patient agrees or declines) before he/she is approached f...

Recent advancements in prosthetic hand technology.

Recently, significant advances over the past decade have been made in robotics, artificial intelligence and other cognitive related fields, allowing d...

Expression of rabies virus glycoprotein in the methylotrophic yeast Pichia pastoris.

Rabies is a fatal disease that can be prevented by vaccination. Different approaches were investigated to develop novel human rabies vaccines with imp...

MicrO: an ontology of phenotypic and metabolic characters, assays, and culture media found in prokaryotic taxonomic descriptions.

BACKGROUND: MicrO is an ontology of microbiological terms, including prokaryotic qualities and processes, material entities (such as cell components),...