Pediatrics

Digital Pathology and Artificial Intelligence in Pediatric Pathology.

Applications of artificial intelligence (AI) and machine learning (ML) are rapidly developing to sup...

Diagnostic Stewardship of Blood Cultures in the Pediatric ICU Using Machine Learning.

OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottl...

Artificial Intelligence in the Clinic: Creating Harmony or Just Adding Noise?

Although still limited, the integration of artificial intelligence (AI) in health care has rapidly e...

Applying an Agile Science Roadmap to Integrate and Evaluate Ethical Frameworks Throughout the Lifecycle and Use of Artificial Intelligence Tools in the Intensive Care Unit.

This article summarizes existing ethical frameworks for healthcare artificial intelligence (AI) and ...

Use of an Untrained Large Language Model for Antibiotic Prescription in Pediatric Infectious Diseases at Primary Care Settings: A Study From the Italian Society for Pediatric Infectious Diseases.

The development of artificial intelligence systems is revolutionizing many fields of medicine, but s...

Glycosyltransferases in human milk oligosaccharide synthesis: structural mechanisms and rational design.

Human milk oligosaccharides (HMOs) play a pivotal role in infant health through their multifunctiona...

Artificial Intelligence (AI) and The Journal of Pediatric and Adolescent Gynecology (JPAG).

Development and Validation of an Explainable Machine Learning Model for Warning of Hepatitis E Virus-Related Acute Liver Failure.

BACKGROUND AND AIMS: Early identification of patients with acute hepatitis E (AHE) who are at high r...

Interpretable deep neural networks for advancing early neonatal birth weight prediction using multimodal maternal factors.

BACKGROUND: Neonatal low birth weight (LBW) is a significant predictor of increased morbidity and mo...

Machine learning models for predicting malnutrition in NICU patients: A comprehensive benchmarking study.

Malnutrition, affecting both adults and children globally, results from inadequate nutrient intake o...

Deep learning-driven imaging of cell division and cell growth across an entire eukaryotic life cycle.

The life cycle of eukaryotic microorganisms involves complex transitions between states such as dorm...

The need for research on AI-driven social media and adolescent mental health.

The increasing integration of artificial intelligence (AI) in social media platforms has transformed...

CellOMaps: A compact representation for robust classification of lung adenocarcinoma growth patterns.

Lung adenocarcinoma (LUAD) is a morphologically heterogeneous disease, characterized by five primary...

Machine Learning for Predicting Waitlist Mortality in Pediatric Heart Transplantation.

BACKGROUND: Waitlist mortality remains a critical issue for pediatric heart transplant (HTx) candida...

Pediatric chest X-ray diagnosis using neuromorphic models.

This research presents an innovative neuromorphic method utilizing Spiking Neural Networks (SNNs) to...

Predictors of smartphone addiction in adolescents with depression: combing the machine learning and moderated mediation model approach.

Smartphone addiction (SA) significantly impacts the physical and mental health of adolescents, and c...

Development of a patient reported outcomes based machine learning model to predict recurrences in head and neck cancer.

INTRODUCTION: Recurrence rates among Head and Neck Cancer (HNC) patients are high, with earlier dete...

Wrist and elbow fracture detection and segmentation by artificial intelligence using point-of-care ultrasound.

PURPOSE: Distal radius (wrist) and supracondylar (elbow) fractures are common in children presenting...

Temporal validation of machine learning models for pre-eclampsia prediction using routinely collected maternal characteristics: A validation study.

BACKGROUND: Pre-eclampsia (PE) contributes to more than one-fourth of all maternal deaths and half a...

An informed deep learning model of the Omicron wave and the impact of vaccination.

The Omicron (B.1.1.529) variant of SARS-CoV-2 emerged in November 2021 and has since evolved into mu...

Comparative analysis of GPT-4 and Google Gemini's consistency with pediatric otolaryngology guidelines.

OBJECTIVE: To evaluate the accuracy and completeness of large language models (LLMs) in interpreting...