Pediatrics

Monitoring Approaches for a Pediatric Chronic Kidney Disease Machine Learning Model.

OBJECTIVE: The purpose of this study is to evaluate the ability of three metrics to monitor for a re...

Camera fusion for real-time temperature monitoring of neonates using deep learning.

The continuous monitoring of vital signs is a crucial aspect of medical care in neonatal intensive c...

A deep learning approach identifies new ECG features in congenital long QT syndrome.

BACKGROUND: Congenital long QT syndrome (LQTS) is a rare heart disease caused by various underlying ...

Attention-modulated multi-branch convolutional neural networks for neonatal brain tissue segmentation.

Accurate measurement of brain structures is essential for the evaluation of neonatal brain growth an...

Pediatric chest radiograph interpretation: how far has artificial intelligence come? A systematic literature review.

Most artificial intelligence (AI) studies have focused primarily on adult imaging, with less attenti...

Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation: Facilitating use of this technology in low resource settings of South Asia and East Africa.

BACKGROUND: Knowledge of gestational age is critical for guiding preterm neonatal care. In the last ...

Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models.

BACKGROUND: Asthma exacerbations are triggered by a variety of clinical and environmental factors, b...

How does artificial intelligence affect green economic growth?-Evidence from China.

As the driving force behind the new wave of technological advancement, artificial intelligence (AI) ...

Automated Machine Learning Pipeline Framework for Classification of Pediatric Functional Nausea Using High-Resolution Electrogastrogram.

OBJECTIVE: Pediatric functional nausea is challenging for patients to manage and for clinicians to t...

Application and potential of artificial intelligence in neonatal medicine.

Neonatal care is becoming increasingly complex with large amounts of rich, routinely recorded physio...

Risk-based implementation of COLREGs for autonomous surface vehicles using deep reinforcement learning.

Autonomous systems are becoming ubiquitous and gaining momentum within the marine sector. Since the ...

A Heterogeneous Ensemble Learning Method For Neuroblastoma Survival Prediction.

Neuroblastoma is a pediatric cancer with high morbidity and mortality. Accurate survival prediction ...

Incidence and resolution of de novo hydronephrosis after pediatric robot-assisted laparoscopic extravesical ureteral reimplantation for primary vesicoureteral reflux.

INTRODUCTION: With the advent of robot-assisted laparoscopic ureteral reimplantation (RALUR) for pri...

Sentimental Analysis of Twitter Users from Turkish Content with Natural Language Processing.

Artificial Intelligence has guided technological progress in recent years; it has shown significant ...

Effects of nitrogen and phosphorus addition on growth and leaf nitrogen metabolism of alfalfa in alkaline soil in Yinchuan Plain of Hetao Basin.

Alkaline soil is widely distributed in China. Its rational utilization is an effective measure to so...

Editorial Comment to Are there disparities in access to robot-assisted laparoscopic surgery among pediatric urology patients? US institutional experience.

SRAS-net: Low-resolution chromosome image classification based on deep learning.

Prenatal karyotype diagnosis is important to determine if the foetus has genetic diseases and some c...

Design and Implementation of Advanced Machine Learning Management and Its Impact on Better Healthcare Services: A Multiple Regression Analysis Approach (MRAA).

In the current information and technology era, business enterprises are focusing in performing the p...

Computational and Mathematical Methods in Medicine Prediction of COVID-19 in BRICS Countries: An Integrated Deep Learning Model of CEEMDAN-R-ILSTM-Elman.

Since the outbreak of COVID-19, BRICS countries have experienced different epidemic spread due to di...

Machine learning to predict effective reaction rates in 3D porous media from pore structural features.

Large discrepancies between well-mixed reaction rates and effective reactions rates estimated under ...

Microfluidic Tissue Engineering and Bio-Actuation.

Bio-hybrid technologies aim to replicate the unique capabilities of biological systems that could su...