Pediatrics

Deep learning architectures for EEG-based classification of Dravet syndrome: A comparative study of pre-trained and non-pretrained hybrid CNN-LSTM models.

OBJECTIVE: This study explores the potential of artificial intelligence (AI) using a hybrid deep learning Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) framework, for EEG-based classification and analysis of Dravet Syndrome (DS). METHOD: The study cohort comprised nine pediatric patients with DS, confirmed through either a heterozygous pathogenic mutation in the SCN1A gene or a cl...

Interferon-Associated Antiviral Programs Define LAG-3+ Exhaustion-Like CD8+ T-Cell Remodeling in Influenza a Virus Infection: An Integrative Single-Cell and Multi-Cohort Analysis.

BACKGROUND: Influenza A virus (IAV) infection induces complex antiviral immune responses, yet how innate sensing, host genetic susceptibility, and adaptive immune dysfunction converge remains incompletely understood. This study investigated peripheral immune remodeling during IAV infection, focusing on LAG-3-expressing CD8+ T cells and their transcriptional and genetic signatures. METHODS: Single-...

Partnering with AI to create joy-centered personalized learning in a post-pandemic world.

STEM instructors are teaching in classrooms shaped by wide variation in students' prior preparation, learning experiences, and well-being, much of whi...

Epigallocatechin gallate inhibits high-fat/choline diet-induced trimethylamine production via regulation of intestinal Serratia and Lactobacillus communities.

High-fat/choline diets can induce the production of the enterogenous metabolite trimethylamine-N-oxide (TMAO). TMAO is synthesized from its precursor ...

Emerging biomarkers in breast fibroadenoma: implications for differential diagnosis, malignant transformation, and precision medicine.

Fibroadenoma is the most common benign fibroepithelial lesion of the breast; it occurs most frequently in adolescents and women of reproductive age. W...

Application of a novel age estimation model based on permanent maxillary canine morphometric features in a Japanese population.

OBJECTIVES: This study aims to clarify the growth curves of the long axis and apical foramen diameter of permanent maxillary canines (PMCs), and to cr...

Smartphone-Based Detection of Abnormal Lung Sounds Using Domain-Adaptive Deep Learning.

Auscultation is a fundamental clinical practice for detecting respiratory abnormalities, but accurate interpretation requires specialized medical expe...

Effect of pilates exercises plus breastfeeding positioning adjustment on artificial intelligence-assessed craniovertebral angle in breastfeeding women with forward head posture: a randomized controlled trial.

Forward head posture (FHP), considered a neuromusculoskeletal disorder, includes those associated with breastfeeding. Pilates is recognized for improv...

MSAFNet: A multi-scale attention fusion network for automated neonatal pain facial expression recognition with clinical validation.

Accurate, timely pain assessment in neonates remains a stubborn yet critical challenge in neonatal intensive care units (NICUs), where conventional ob...

Retrieval-Augmented Generation in Radiology: A Scoping Review of Architectures, Imaging Applications, and Directions for Equitable Deployment.

Large language models (LLMs) are increasingly explored in radiology, yet concerns persist regarding hallucination and lack of factual grounding. Retri...

A primer on artificial intelligence for palliative care educators.

Artificial intelligence (AI) is rapidly being adopted in education in the health care professions, including in palliative care. Yet existing AI prime...

Neonatal Bloodstream Infections: A Narrative Review on Diagnostic and Therapeutic Challenges and Prospects in Developing Countries.

BACKGROUND: Bloodstream infections (BSIs) pose a significant global health challenge, particularly in developing countries. Neonates are highly vulner...

Do Large Language Models Support Nursing Care Planning? A Scoping Review of Applications, Evaluation Approaches and Outcomes.

AIM: To examine the overall performance of large language models (LLMs) in generating nursing care plans, clarify their role in nursing practice and i...

The Use of Artificial Intelligence in Neonatal Seizure Detection: An Artificial Intelligence-Assisted Systematic Review.

BACKGROUND: Artificial intelligence (AI) is increasingly used in health care. We systematically reviewed evidence on the accuracy of AI in detecting n...

Reach: Recognising episodes of acute complexity in health: a predictive older patient prioritisation machine learning model.

As the numbers of older people (65 +) rise globally, the pressure on acute hospitals to provide efficient and effective care while addressing resource...

The Ways in Which Stakeholders Make Decisions About AI and Novel Technologies for the Health Care of Older Adults: Qualitative Interview Study.

BACKGROUND: Artificial intelligence (AI) has the potential to improve health among older adults, yet how different stakeholders decide to develop, fin...

Performance of 5 Large Language Models in Perioperative Consultation for Pediatric Hypospadias: Cross-Sectional Comparative Study.

BACKGROUND: Hypospadias is a common congenital malformation requiring surgery. Caregivers face substantial perioperative information needs, and large ...

Examining the Roles of Technology Across the Health Care Journey for Individuals With Obsessive-Compulsive Disorder: Qualitative Interview Study.

BACKGROUND: As digital technologies become increasingly embedded in daily life, their roles in mental health care have expanded and diversified. Digit...

Uncertainty-Aware Risk Stratification in Pediatric Low-Grade Glioma Using Multimodal Data.

BACKGROUND AND PURPOSE: Risk stratification in pediatric low-grade glioma (pLGG) remains challenging due to biological and clinical heterogeneity. We ...

Artificial intelligence for pediatric fracture detection: impact on diagnostic revisions and patient recall rates in a tertiary emergency setting.

PURPOSE: Artificial intelligence (AI) can support and enhance radiologists in musculoskeletal imaging, but evidence of clinical benefit is still lacki...