Pediatrics

Exploring and validating hub genes associated with atopic dermatitis through weighted gene co-expression network analysis and machine learning.

This study aimed to identify novel biomarkers of atopic dermatitis (AD) and investigate their pathogenic mechanisms. We analyzed 7 AD-related datasets from the gene expression omnibus database and identified overlapping differentially expressed genes through integrated analysis of differential expression and weighted gene co-expression networks. Functional enrichment analysis revealed that these g...

Radiological assessment of pulmonary vascularity in congenital heart disease: standardized clinician assessment versus deep learning-based prediction.

BACKGROUND: Assessment of pulmonary vascularity on chest radiographs (CXRs) in congenital heart disease (CHD) is limited by subjectivity, and existing criteria lack sufficient validation. Artificial intelligence-based deep learning model (DLM) analysis may improve accuracy. We developed and validated structured criteria and a DLM to evaluate pulmonary vascularity and compared it with conventional ...

Temporal shifts in public perceptions of influenza and its vaccine before, during, and after COVID-19 in a fragile nation.

BACKGROUND: Since the emergence of the COVID-19 pandemic, co-infection with COVID-19 and influenza has been associated with adverse health and economi...

Artificial Intelligence in Simulation Design: The Effectiveness of a Customized Artificial Intelligence-based Scenario Development Tool.

INTRODUCTION: The creation of simulation scenarios is typically time-consuming and requires a high cognitive load. Artificial intelligence (AI) and la...

Describing Candidate Geographic Atrophy Phenotypes and Their Different Growth Parameters.

PURPOSE: Describe distinct candidate geographic atrophy (GA) phenotypes in age-related macular degeneration (AMD) and their different growth parameter...

Ethics of artificial intelligence prognostication in palliative care: perspectives from a national survey of palliative care physicians.

OBJECTIVES: Artificial intelligence (AI) tools have the potential to transform access to and delivery of palliative care globally-an urgent unmet need...

Skin-to-skin contact improves sleep stability in preterm infants.

BACKGROUND: Sleep supports neurophysiological maturation in preterm infants, yet the impact of developmental care interventions on sleep remains poorl...

The Value Opportunity from Artificial Intelligence in U.S. Health Care Spending.

Artificial intelligence (AI) offers the potential to improve productivity and reduce waste across the U.S. health care system. Quantifying achievable ...

How Social Media Analysis Offers an Opportunity to Understand the Reality of People Living With Multiple Sclerosis: Descriptive French Study.

BACKGROUND: Multiple sclerosis (MS) is a chronic neurological disease that starts in young adulthood and can significantly affect quality of life (QoL...

Automated Post-Analytical Workflow for Newborn Screening Using a Hybrid Rule-Based and Retrieval-Augmented Large Language Model System.

Newborn screening using tandem mass spectrometry requires complex post-analytical workflows, including QC review, patient report generation, and cutof...

Piezo1 channel: structure, mechanogating mechanism, functions, diseases and therapeutic strategy.

The Piezo1 channel is a mechanosensitive, non-selective cation channel that converts mechanical forces into electrochemical signals, playing pivotal r...

The Continuity Trap in Data Science Health Research.

Secondary use is now the ordinary condition of data science health research rather than an exception to it. Electronic health records collected for cl...

Upstream costs of the energy transition: differentiated mechanisms of economic-environmental synergy in lithium development systems.

As the global energy transition accelerates, the low-carbon benefits realized downstream in new energy supply chains do not mean that upstream resourc...

The Reliability of Human Evaluation of Large Language Models in Health Care Settings: Scoping Review.

BACKGROUND: Integration of large language models (LLMs) into health care has accelerated rapidly, yet reliability concerns pose potential risks to pat...

Development and evaluation of AI-based clinical decision support system for streamlining breast multidisciplinary team meetings.

OBJECTIVES: Multidisciplinary team (MDT) meetings are key to delivering cancer care. Increasing caseload and limited resources make them less effectiv...

Real-Time AI Voice Translation for International Medical Conferences and Beyond: Enabling Multilingual Scientific Exchange.

BACKGROUND: Language barriers continue to limit participation in international medical communication, and recent advances in artificial intelligence n...

Artificial Intelligence in Ultrasound Imaging: Opportunities for Improving Diagnostic Accuracy in Gulf Health Care.

Ultrasound imaging is widely used across cardiology, hepatology, obstetrics, breast and thyroid imaging, and emergency care because it is real-time, n...

Tracking funding disparities in global health aid with machine learning.

Reducing the global burden of disease is crucial for improving health outcomes. However, misalignment between health aid and country-level disease bur...

Multimodal Digital Therapeutics Enhanced by Task Design and AI for Attention-Deficit/Hyperactivity Disorder Core Symptoms and Executive Functions in Children and Adolescents: Systematic Review and Network Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children and adolescents. Digital therapeuti...

Prognostication in End-Stage Kidney Disease: Tools, Evidence, and Clinical Applications.

Prognostication in end-stage kidney disease is fundamental to person-centered care and shared decision-making. This review summarizes the current evid...