Pediatrics

Utilization of Random Forest and Deep Learning Neural Network for Predicting Factors Affecting Perceived Usability of a COVID-19 Contact Tracing Mobile Application in Thailand "ThaiChana".

The continuous rise of the COVID-19 Omicron cases despite the vaccination program available has been progressing worldwide. To mitigate the COVID-19 contraction, different contact tracing applications have been utilized such as Thai Chana from Thailand. This study aimed to predict factors affecting the perceived usability of Thai Chana by integrating the Protection Motivation Theory and Technology...

[The role of bile acid measurement in the management of intrahepatic cholestasis of pregnancy].

Introduction: Intrahepatic cholestasis of pregnancy complicates 1% of pregnancies. It increases the risk of severe fetal complications significantly, including preterm delivery and stillbirth. Objective: To summarize our experience with serum total bile acid level measurement that has recently become available for clinical routine in Hungary, and to present the way of gestational cholestasis care ...

Parental Perceptions on Use of Artificial Intelligence in Pediatric Acute Care.

BACKGROUND: Family engagement is critical in the implementation of artificial intelligence (AI)-based clinical decision support tools, which will play...

Learned iterative segmentation of highly variable anatomy from limited data: Applications to whole heart segmentation for congenital heart disease.

Training deep learning models that segment an image in one step typically requires a large collection of manually annotated images that captures the a...

Prosit-TMT: Deep Learning Boosts Identification of TMT-Labeled Peptides.

The prediction of fragment ion intensities and retention time of peptides has gained significant attention over the past few years. However, the progr...

Vaccine Therapy in Non-Small Cell Lung Cancer.

Immunotherapy using immune checkpoint modulators has revolutionized the oncology field, emerging as a new standard of care for multiple indications, i...

A Study on Cross-Media Teaching Model for College English Classroom Based on Output-Driven Hypothetical Neural Network.

In the field of education, the development of educational big data has become an important strategic choice to promote the construction of the digital...

Automated segmentation of whole-body CT images for body composition analysis in pediatric patients using a deep neural network.

OBJECTIVES: To develop an automatic segmentation algorithm using a deep neural network with transfer learning applicable to whole-body PET-CT images i...

Retraining an Artificial Intelligence Algorithm to Calculate Left Ventricular Ejection Fraction in Pediatrics.

OBJECTIVES: Identifying patients with low left ventricular ejection fraction (LVEF) and monitoring LVEF responses to treatment are important clinical ...

Automated detection of acute appendicular skeletal fractures in pediatric patients using deep learning.

OBJECTIVE: We aimed to perform an external validation of an existing commercial AI software program (BoneView™) for the detection of acute appendicula...

New meaning for NLP: the trials and tribulations of natural language processing with GPT-3 in ophthalmology.

Natural language processing (NLP) is a subfield of machine intelligence focused on the interaction of human language with computer systems. NLP has re...

Evaluation of Smart City Sustainable Development Prospects Based on Fuzzy Comprehensive Evaluation Method.

In this study, the method of a fuzzy comprehensive evaluation is used to analyze the research situation of smart city development, and 20 evaluation i...

Aspect Based Twitter Sentiment Analysis on Vaccination and Vaccine Types in COVID-19 Pandemic With Deep Learning.

Due to the COVID-19 pandemic, vaccine development and community vaccination studies are carried out all over the world. At this stage, the opposition ...

V08-07 Robotic Pyeloplasty of Lower Pole Moiety in a 2 Month Old Infant With Cutaneous Pyeloureteral (CPU) Stent. Erratum.

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 reduction in performance of a chronic kidney disease...

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 care units. Since cable-based sensors pose a potent...

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 mutations. Most general cardiologists do not routi...

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 and development. The conventional methods use manual...

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 attention to the unique aspects of pediatric imaging. The...

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 decade, metabolic gestational dating approaches em...