Pediatrics

Prompting the future: artificial intelligence in pediatric radiology.

Prediction of pediatric lower urinary tract dysfunction using uroflowmetry data and machine learning with explainable AI techniques.

PURPOSE: To develop and evaluate a machine learning-based approach for the interpretation of uroflowmetry in pediatric lower urinary tract dysfunction, aiming to reduce interobserver variability and improve diagnostic consistency while maintaining clinical interpretability. METHODS: In this single-center retrospective study, 2663 pediatric uroflowmetry records (age 2-18 years, July 2019-March 2024...

Value of AI in Critical Care Using Real-World Evidence on Intensive Care Unit Mortality Prediction: Cost-Utility Analysis.

BACKGROUND: AI-based models for predicting mortality have shown potential for intensive care unit (ICU) patients, but evidence regarding their cost-ef...

Deep learning applications in osteosarcoma MRI: A systematic review of recent advances in AI-based osteosarcoma diagnosis.

Primary malignant bone tumours of the skeleton have a great diversity in their biological behaviour, and the most common in adolescence is osteosarcom...

A Generational Approach to Neurology Education: Engaging Generation Z Learners.

Neurophobia remains a persistent barrier in neurology education because learners often struggle to connect neuroanatomy, localization, examination fin...

Seizure detection using hierarchical temporal trend integration and self-supervised learning.

Early, reliable detection of epileptic seizures from electroencephalography (EEG) remains challenging due to label scarcity, inter patient variability...

An explainable biomedical foundation model via large-scale concept-enhanced vision-language pretraining.

Artificial intelligence for medical imaging is required to be accurate and interpretable to clinicians. However, current multimodal biomedical foundat...

Comparison of a Computable Pediatric Sepsis Phenotype Tool in Argentinian and U.S. Cohorts.

OBJECTIVE: Sepsis is a leading cause of mortality in low- and middle-income countries. This study identifies computable pediatric sepsis phenotypes (P...

Patient-Specific Non-Invasive Epileptogenic Zone Localization via High-Resolution Time-Frequency Representations and CNN Deep Learning.

Stereoelectroencephalography (SEEG)-guided radiofrequency thermocoagulation is the mainstream treatment for drug-resistant epilepsy (DRE), yet non-inv...

The Use of Machine Learning in Pediatric Research.

Long-term PM2.5 exposure and leukemia risk from childhood to early adulthood: A nationwide longitudinal cohort study with time-varying exposure analysis.

Long-term exposure to fine particulate matter (PM2.5) has been suggested as an environmental risk factor for childhood leukemia. This study examined t...

Adapt or Become Irrelevant: the Pathologist as the new Diagnostic Architect.

AIMS: Pathology is undergoing a paradigm shift as diagnostics become increasingly multimodal and computational. Yet legacy structures, incentives and ...

Local Chemistry-Guided Molecular Beam Epitaxy Growth of SnSe on MgO via Combined ReaxFF Modeling and Machine Learning.

Subtle variations in local growth chemistry can fundamentally alter the morphology of layered chalcogenide thin films, yet the atomic-scale mechanisms...

Clinical Subphenotypes and Short-Term Outcomes in PICU Patients Receiving Continuous Blood Purification.

OBJECTIVES: To characterize clinical heterogeneity among PICU patients receiving continuous blood purification (CBP) and identify data-driven subpheno...

Artificial Intelligence and Machine Learning-based prediction of tuberculosis treatment failure: A systematic review and meta-analysis.

BACKGROUND: Tuberculosis (TB) remains a leading cause of infectious disease mortality worldwide, and treatment failure contributes to ongoing transmis...

Artificial Intelligence and Nursing: Freedom From the Mundane or Subservience to a New Nobility.

AIM: To explore the notion of post-humanism and the impact of artificial intelligence (AI) on society, nursing and healthcare. DESIGN: Discursive pape...

Modeling the development of English reading enjoyment in AI-mediated IDLE: A complex dynamic systems theory perspective.

As artificial intelligence (AI) becomes increasingly integrated into English learning, AI-supported informal digital environments have emerged as an i...

Understanding the Experiences of Young People Living With Haemophilia-A UK Social Media Study.

INTRODUCTION: Haemophilia is a rare congenital bleeding disorder that presents significant physical and psychological challenges, especially for young...

The American Cancer Society National Lung Cancer Roundtable strategic plan: Opportunities in advanced imaging across the lung cancer care continuum.

Lung cancer is the leading cause of cancer death in men and women. The goal of reducing mortality from lung cancer requires improvements in many aspec...

Emerging and Re-Emerging Viral Infections in Poultry: Integrating Traditional and AI-Based Control Strategies.

Poultry production remains significantly challenged by emerging and re-emerging avian viral diseases, which are influenced by host-pathogen interactio...