Pediatrics

Review of Machine Learning and Artificial Intelligence (ML/AI) for the Pediatric Neurologist.

Artificial intelligence (AI) and a popular branch of AI known as machine learning (ML) are increasingly being utilized in medicine and to inform medical research. This review provides an overview of AI and ML (AI/ML), including definitions of common terms. We discuss the history of AI and provide instances of how AI/ML can be applied to pediatric neurology. Examples include imaging in neuro-oncolo...

Research on the development trend, evolution, and spatial local characteristics of the intelligent smart medical industry in the Yangtze River Economic Belt.

A comprehensive survey of the development trends, trend evolution, and spatial non-equilibrium characteristics of the intelligent smart medical industry in the Yangtze River Economic Belt could provide significant policy implications for optimizing the spatial layout of the integrated development of the smart medical industry in this region. Using the Criteria Importance Though Intercriteria Corre...

PhenoBot: an automated system for leaf area analysis using deep learning.

A low-cost dynamic image capturing and analysis pipeline using color-based deep learning segmentation was developed for direct leaf area estimation of...

Comparison of the Physical Care Burden on Formal Caregivers between Manual Human Care Using a Paper Diaper and Robot-Aided Care in Excretion Care.

Although the older population has been rapidly growing, the availability of formal caregivers remains limited. Assistance provided by care robots has ...

The effect of the pandemic on European narratives on smart cities and surveillance.

This article presents an analysis of European smart city narratives and how they evolved under the pressure of the COVID-19 pandemic. We start with Jo...

AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging.

Rapid advances in artificial intelligence (AI) and machine learning, and specifically in deep learning (DL) techniques, have enabled broad application...

Hospital crowdedness evaluation and in-hospital resource allocation based on image recognition technology.

How to allocate the existing medical resources reasonably, alleviate hospital congestion and improve the patient experience are problems faced by all ...

Deep Learning-Based Multiclass Brain Tissue Segmentation in Fetal MRIs.

Fetal brain tissue segmentation is essential for quantifying the presence of congenital disorders in the developing fetus. Manual segmentation of feta...

Early experience with low-pass filtered images facilitates visual category learning in a neural network model.

Humans are born with very low contrast sensitivity, meaning that inputs to the infant visual system are both blurry and low contrast. Is this solely a...

Ethical considerations of using artificial intelligence to drive clinical decision support in pediatric medical settings.

Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring: Part 1 wearable technology.

With the development of Artificial Intelligence techniques, smart health monitoring is becoming more popular. In this study, we investigate the trend ...

Considerations for Creating a Restricted Data Environment with Complete Primary Care Electronic Medical Record Data.

Background: Historically, primary care databases have been limited to subsets of the full electronic medical record (EMR) data to maintain privacy. Wi...

Explainable Machine Learning Model to Predict COVID-19 Severity Among Older Adults in the Province of Quebec.

Context: Patients over the age of 65 years are more likely to experience higher severity and mortality rates than other populations from COVID-19. Cli...

High throughput optimization of medium composition for Escherichia coli protein expression using deep learning and Bayesian optimization.

To improve synthetic media for protein expression in Escherichia coli, a strategy using deep neural networks (DNN) and Bayesian optimization was perfo...

Deep Learning on Multiphysical Features and Hemodynamic Modeling for Abdominal Aortic Aneurysm Growth Prediction.

Prediction of abdominal aortic aneurysm (AAA) growth is of essential importance for the early treatment and surgical intervention of AAA. Capturing ke...

Painless and accurate medical image analysis using deep reinforcement learning with task-oriented homogenized automatic pre-processing.

Pre-processing is widely applied in medical image analysis to remove the interference information. However, the existing pre-processing solutions main...

An accurate deep learning model for wheezing in children using real world data.

Auscultation is an important diagnostic method for lung diseases. However, it is a subjective modality and requires a high degree of expertise. To ove...

Accuracy of computer-assisted pedicle screw placement for adolescent idiopathic scoliosis: a comparison between robotics and navigation.

PURPOSE: To compare the accuracy of pedicle screw placement in adolescent idiopathic scoliosis (AIS) between robotics and navigation and clarify the f...

Automated quantitative assessment of pediatric blunt hepatic trauma by deep learning-based CT volumetry.

BACKGROUND: To develop an end-to-end deep learning method for automated quantitative assessment of pediatric blunt hepatic trauma based on contrast-en...

Application of percutaneous nephrolithotomy combined with da Vinci Xi robot in complicated upper urinary tract repair surgery: A case report.

Duplex kidney and ureter is a congenital malformation. Few patients present with hydronephrosis caused by obstruction of the ureteropelvic junction of...