Pediatrics

Assessing ChatGPT Responses to Frequently Asked Questions Regarding Pediatric Supracondylar Humerus Fractures.

BACKGROUND: The internet and standard search engines are commonly used resources for patients seeking medical information online. With the advancement and increasing usage of artificial intelligence (AI) in health information, online AI chatbots such as ChatGPT may surpass traditional web search engines as the next go-to online resource for medical information. This study aims to assess the abilit...

Improving entity recognition using ensembles of deep learning and fine-tuned large language models: A case study on adverse event extraction from VAERS and social media.

OBJECTIVE: Adverse event (AE) extraction following COVID-19 vaccines from text data is crucial for monitoring and analyzing the safety profiles of immunizations, identifying potential risks and ensuring the safe use of these products. Traditional deep learning models are adept at learning intricate feature representations and dependencies in sequential data, but often require extensive labeled dat...

Video Clip Extraction From Fetal Ultrasound Scans Using Artificial Intelligence to Allow Remote Second Expert Review for Congenital Heart Disease.

OBJECTIVE: To use artificial intelligence (AI) to automatically extract video clips of the fetal heart from a stream of ultrasound video, and to asses...

Applying machine learning to ecological momentary assessment data to identify predictors of loss-of-control eating and overeating severity in adolescents: A preliminary investigation.

OBJECTIVE: Several factors (e.g., interpersonal stress, affect) predict loss-of-control (LOC) eating and overeating in adolescents, but most past rese...

Initializing a Public Repository for Hosting Benchmark Datasets to Facilitate Machine Learning Model Development in Food Safety.

While there is clear potential for artificial intelligence (AI) and machine learning (ML) models to help improve food safety, the development and depl...

Machine Learning-Based Pediatric Early Warning Score: Patient Outcomes in a Pre- Versus Post-Implementation Study, 2019-2023.

OBJECTIVES: To describe the deployment of pediatric Calculated Assessment of Risk and Triage (pCART), a machine learning (ML) model to predict the ris...

A living scoping review and online repository of artificial intelligence models in pediatric urology: Results from the AI-PEDURO collaborative.

INTRODUCTION: Artificial intelligence (AI) is increasingly being applied across pediatric urology. We provide a living scoping review and online repos...

Interoperable Models for Identifying Critically Ill Children at Risk of Neurologic Morbidity.

IMPORTANCE: Decreasing mortality in the field of pediatric critical care medicine has shifted practicing clinicians' attention to preserving patients'...

Harmonizing flows: Leveraging normalizing flows for unsupervised and source-free MRI harmonization.

Lack of standardization and various intrinsic parameters for magnetic resonance (MR) image acquisition results in heterogeneous images across differen...

Development and validation of fully automated robust deep learning models for multi-organ segmentation from whole-body CT images.

PURPOSE: This study aimed to develop a deep-learning framework to generate multi-organ masks from CT images in adult and pediatric patients.

Artificial intelligence in surgery: evolution, trends, and future directions.

Artificial intelligence (AI) is significantly transforming surgery by enhancing precision, decision-making, and patient outcomes. This bibliometric an...

Visual collective behaviors on spherical robots.

The implementation of collective motion, traditionally, disregard the limited sensing capabilities of an individual, to instead assuming an omniscient...

Adjacent point aided vertebral landmark detection and Cobb angle measurement for automated AIS diagnosis.

Adolescent Idiopathic Scoliosis (AIS) is a prevalent structural deformity disease of human spine, and accurate assessment of spinal anatomical paramet...

High resolution multi-delay arterial spin labeling with self-supervised deep learning denoising for pediatric choroid plexus perfusion MRI.

Choroid plexus (CP) is an important brain structure that produces cerebrospinal fluid (CSF). CP perfusion has been studied using multi-delay arterial ...

Identification of Intracranial Germ Cell Tumors Based on Facial Photos: Exploratory Study on the Use of Deep Learning for Software Development.

BACKGROUND: Primary intracranial germ cell tumors (iGCTs) are highly malignant brain tumors that predominantly occur in children and adolescents, with...

Elucidating the Mechanism of VVTT Infection Through Machine Learning and Transcriptome Analysis.

The vaccinia virus (VV) is extensively utilized as a vaccine vector in the treatment of various infectious diseases, cardiovascular diseases, immunode...

Ultrasound and histopathological assessment of benign, borderline, and malignant thyroid tumors in pediatric patients: an illustrative review and literature overview.

BACKGROUND: The risk of malignancy in thyroid nodules is higher in children than in adults, often necessitating a more aggressive endocrine and surgic...

Paradigms of intraoperative neuromonitoring in paediatric thyroid surgery.

The larynx of children and adolescents is still in the developmental phase and the anatomical structure is still very small and sensitive. The higher ...

Artificial Intelligence in Fetal Growth Restriction Management: A Narrative Review.

This narrative review examines the integration of Artificial Intelligence (AI) in prenatal care, particularly in managing pregnancies complicated by F...

DSAM: A deep learning framework for analyzing temporal and spatial dynamics in brain networks.

Resting-state functional magnetic resonance imaging (rs-fMRI) is a noninvasive technique pivotal for understanding human neural mechanisms of intricat...