Pediatrics

Agreement between three state-of-the-art deep learning bone age estimation models and chronological age in a large contemporary pediatric cohort.

BACKGROUND: Radiographic bone age estimation is routinely performed in children to evaluate short stature, early or late puberty, and endocrine disorders, as well as for surgical planning. OBJECTIVE: To evaluate agreement between three state-of-the-art deep learning bone age estimation models and chronological age in a large contemporary pediatric cohort. MATERIALS AND METHODS: We retrospectively ...

pedQTNet: A Deep Learning Approach to Estimate Corrected QT Intervals from Multi-Lead Conventional ECG Waveforms in Pediatric Patients.

Long QT syndrome (LQTS) is a primary risk factor for ventricular arrhythmias and sudden cardiac death in children. Accurate corrected QT intervals (QTc) measurement is imperative but challenging for non-heart-rhythm specialists, especially in children. We developed and evaluated pedQTNet, a deep neural network model for estimating QTc and detecting LQTS in pediatric patients. We analyzed a cohort ...

Moving From Keywords to Contextual Meaning: A Commentary on Hybrid Bibliometric Synthesis in Health Research.

The fast growth of social media mining in health research has contributed to an invaluable but quite fragmented body of literature. As the amount of u...

Forecasting the Impacts of Artificial Intelligence Assistance in Virtual Consultations for Chronic Obstructive Pulmonary Disease: Exploratory Futures Wheel Study.

BACKGROUND: While digital health technologies promise to reshape the medical journey, their potential might not be realized due to unforeseen implemen...

The Influence of Social Media Messaging on Human Papillomavirus Vaccine Attitudes and Confidence Among Adolescent Males: Group Discussion Study.

BACKGROUND: Despite the human papillomavirus (HPV) vaccine being available to males for the past 12 years, adolescent males continue to lag in HPV vac...

Continuous optimization strategies based on data insights an analysis of LinkedIn' s operational model.

This paper investigates LinkedIn's continuous optimization strategies driven by data insights, with a focus on how algorithmic personalization, real-t...

Dual swin transformer for assisting in the diagnosis and surgical prediction of necrotizing enterocolitis.

BACKGROUND: The diagnosis and surgical prediction of necrotizing enterocolitis (NEC) remain challenging. Our goal is to develop an interpretable multi...

Integrating multisequence radiomics and clinical features to predict seizure recurrence after gross total resection of pediatric low-grade epilepsy-associated brain tumors.

OBJECTIVE: This study aimed to develop a predictive model integrating clinical features and multisequence MRI radiomics to forecast postoperative seiz...

Deep learning-based automated assessment of pulmonary artery indices and surgical approach triage for tetralogy of Fallot from multicenter cardiac computed tomography (CT).

AIM: To develop an automated framework for deep learning (DL)-based segmentation, pulmonary artery indices (PAIs) computation, and rule-based surgical...

Leveraging large language models in patient-reported outcome measure development: practical opportunities, cautions, and a human-in-the-loop roadmap.

BACKGROUND: Patient-reported outcome (PRO) measure development involves multiple language-intensive stages, including conceptual domain definition, ca...

Ultrasound elastography in pediatric care: bridging innovation and noninvasive diagnostics.

This review explores the application and limitations of ultrasound elastography (USE) in the pediatric population, addressing its diagnostic value acr...

Specific-Source Insights into Changes of O3 Concentrations and Health Risks in China.

Quantifying source-specific ozone concentrations is essential for formulating precursor emission control policies and assessing associated health risk...

Symbolic Acceleration and Embodied Integration: Toward a Developmental Framework of Identity Reconstruction.

Identity is a multi-level integrative process involving coordinated development across affective, symbolic, and embodied systems-a process of progress...

Readiness Assessment for AI in Nursing Care Projects: Multimethods Study.

BACKGROUND: Integrating artificial intelligence (AI) systems into nursing care often encounters obstacles stemming from unmet requirements and insuffi...

Hybrid Modeling for Industrial Fermentation Processes with an 'Intra-Batch Experimental Design'.

Successful development of a predictive digital twin or digital shadow enabling improved batch planning and process optimization of industrial fungal f...

AmygdalaGo-BOLT for boundary-aware segmentation of the human amygdala.

Tracing the boundaries of the amygdala from brain images remains a major challenge in human neuroscience. Although large-scale neuroimaging studies in...

AI-derived versus surgeon-performed instrumentation in adolescent idiopathic scoliosis: a biomechanical simulation analysis.

PURPOSE: Posterior spinal fusion (PSF) with pedicle screws is the standard treatment for adolescent idiopathic scoliosis (AIS) with curves > 45°, yet ...

Predicting knowledge of cervical cancer screening among reproductive-age women in sub-saharan africa using machine learning algorithms.

Sub-Saharan Africa faces twice the incidence and up to fifteen times the fatality rate of cervical cancer compared to developed countries. Screening c...

[Diagnosis and treatment for congenital ossicular chain malformations: current status, challenges, and future prospects].

Congenital ossicular chain malformation constitutes a pivotal etiological factor in conductive hearing loss. Despite its relatively low clinical incid...

Mental health in early pregnancy: Interplay of objectively measured lifestyles, gut microbiota, and metabolomics.

Prenatal anxiety symptoms (AS) and depression symptoms (DS) in early pregnancy substantially impact maternal-infant health, but their pathophysiologic...