Pediatrics

Reinforcement learning relieves the vaccination dilemma.

The main goal of this paper is to study how a decision-making rule for vaccination can affect epidemic spreading by exploiting the Bush-Mosteller (BM) model, one of the methodologies in reinforcement learning in artificial intelligence (AI), which can realize the systematic process of learning in humans, on complex networks. We consider the BM model with two stages-vaccination and epidemiological ...

Automated Matching of Patients to Clinical Trials: A Patient-Centric Natural Language Processing Approach for Pediatric Leukemia.

PURPOSE: Matching patients to clinical trials is cumbersome and costly. Attempts have been made to automate the matching process; however, most have used a trial-centric approach, which focuses on a single trial. In this study, we developed a patient-centric matching tool that matches patient-specific demographic and clinical information with free-text clinical trial inclusion and exclusion criter...

A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea.

Characterization of sleep stages is essential in the diagnosis of sleep-related disorders but relies on manual scoring of overnight polysomnography (P...

Pose Tracking of Supermicrosurgical Robot Towards Multi-User Teleoperation.

This paper presents pose tracking experiments using a supermicrosurgical robot designed to consider teleoperation with multiple surgeons. Currently, e...

2D Wavelet-Scalogram Deep-Learning for Seizures Pattern Identification in the Post-Hypoxic-Ischemic EEG of Preterm Fetal Sheep.

Neonatal seizures after an hypoxic-ischemic (HI) event in preterm newborns can contribute to neural injury and cause impaired brain development. Prete...

Deep-Learning Markerless Tracking of Infant General Movements using Standard Video Recordings.

Monitoring spontaneous General Movements (GM) of infants 6-20 weeks post-term age is a reliable tool to assess the quality of neurodevelopment in earl...

Bone age assessment from articular surface and epiphysis using deep neural networks.

Bone age assessment is of great significance to genetic diagnosis and endocrine diseases. Traditional bone age diagnosis mainly relies on experienced ...

Artificial Intelligence and the Future of Dentistry.

"Narrow" artificial intelligence (AI), as opposed to "general" AI, keenly focuses on a single task and performs that task extremely well, such that it...

Artificial Intelligence in Pediatric Endoscopy: Current Status and Future Applications.

The application of artificial intelligence (AI) has great promise for improving pediatric endoscopy. The majority of preclinical studies have been und...

Improving Methods of Identifying Anaphylaxis for Medical Product Safety Surveillance Using Natural Language Processing and Machine Learning.

We sought to determine whether machine learning and natural language processing (NLP) applied to electronic medical records could improve performance ...

Tracing human life trajectory using gut microbial communities by context-aware deep learning.

The gut microbial communities are highly plastic throughout life, and the human gut microbial communities show spatial-temporal dynamic patterns at di...

A novel method for conformity assessment testing of infant incubators for post-market surveillance purposes.

BACKGROUND: Premature born infants or infants born sick require immediate medical attention and decreasing the stress imposed onto their body by the e...

Artificial intelligence and machine learning in ophthalmology: A review.

Since the introduction of artificial intelligence (AI) in 1956 by John McCarthy, the field has propelled medicine, optimized efficiency, and led to te...

A Guide to MethylationToActivity: A Deep Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes in Individual Tumors.

Genome-wide DNA methylomes have contributed greatly to tumor detection and subclassification. However, interpreting the biological impact of the DNA m...

Deep learning image reconstruction for quality assessment of iodine concentration in computed tomography: A phantom study.

BACKGROUND: Recently, deep learning reconstruction (DLR) technology aiming to improve image quality with minimal radiation dose has been applied not o...

Analysis of COVID-19 Vaccinations and Symptom Mapping Diagnostic Technique for Viral Diseases: Using Data Analytics, Machine Learning, and Artificial Intelligence.

To analyze, understand, and measure the COVID-19 vaccination outlook in a developing country as Nigeria; and the non-clinical analysis, diagnosis, tre...

Assessing the Competence of Artificial Intelligence Programs in Pediatric Ophthalmology and Strabismus and Comparing their Relative Advantages.

The aim of the study was to determine the knowledge levels of ChatGPT, Bing, and Bard artificial intelligence programs produced by three different ma...

New technologies in airway management: A review.

The evolution of medical knowledge and technological growth have contributed to the development of different techniques and devices for airway managem...

An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation.

BACKGROUND: Electroencephalogram (EEG) monitoring is recommended as routine in newborn neurocritical care to facilitate early therapeutic decisions an...

Artificial Intelligence-based Detection of Epileptic Discharges from Pediatric Scalp Electroencephalograms: A Pilot Study.

We developed an artificial intelligence (AI) technique to identify epileptic discharges (spikes) in pediatric scalp electroencephalograms (EEGs). We b...