Pediatrics

A machine learning approach to using ultrasound for body composition and nutritional status assessment in newborns: a pilot study protocol.

BACKGROUND: Accurate assessment of infant body composition, specifically fat and fat-free mass, is c...

Identifying minimal risk factors for adolescent suicidal ideation and suicide attempts: A machine learning-optimized approach.

This study aimed to develop and validate a machine learning (ML) model to identify the minimal risk ...

Beyond exam accuracy: Tracking a persistent-failure set reveals visual dental reasoning gaps in multimodal LLMs.

OBJECTIVES: To benchmark late-2025 general-purpose multimodal large language models (LLMs) on the Ja...

Real-time deep learning interpretation of echocardiographic video for automated detection of anatomical features associated with tetralogy of fallot in pediatric patients : a feasibility study.

Challenges in translating AI-driven ASD/ADHD diagnosis: A methodological systematic review.

BACKGROUND: Early and accurate diagnosis of neurodevelopmental disorders (NDDs), including autism sp...

The relationship between artificial intelligence literacy and artificial intelligence anxiety: A cross-sectional study among pediatric nurses.

AIM: This study aimed to investigate the relationship between pediatric nurses' levels of artificial...

Generation of virtual abdominal aortic aneurysm shape evolution using a physics-based G&R model and its applications to aneurysm growth prediction.

The computational growth and remodeling (G&R) of aortic aneurysms has been extensively investigated ...

Genomic and evolutionary factors influencing the prediction accuracy of optimal growth temperature in prokaryotes.

Bacteria and archaea have evolved diverse genomic adaptations to thrive across various temperatures....

Predicting Ketamine Exposure in Pediatric Status Epilepticus: A Pharmacokinetic-Machine Learning Approach.

BACKGROUND AND OBJECTIVE: Status epilepticus is a life-threatening neurological emergency. Ketamine ...

Automatic lateral ventricle and choroid plexus segmentation method in infant brain MR images.

INTRODUCTION: Accurate segmentation of the lateral ventricles (LV) and choroid plexus (CP) in infant...

Machine learning-based prediction model for risk factors associated with conversion to open surgery in pediatric laparoscopic radical resection of choledochal cysts.

Identifying researcher characteristics driving growth in Japanese University-originated deep-tech startups: A machine learning approach.

Active involvement of researchers with strong outputs is essential for growth of deep-tech universit...

Multicenter Histology Image Integration and Multiscale Deep Learning Support Machine Learning-Enabled Pediatric Sarcoma Classification.

UNLABELLED: Pediatric sarcomas present diagnostic challenges due to their rarity and diverse subtype...

Fuzzy-logic-driven predictions of multi-tissue ingrowth for rapid screening of mechanically instructive tissue-engineering scaffolds.

High retear rates in surgical intervention of interfacial/transitional tissues (bone-tendon, bone-li...

Generative artificial intelligence in medical scientific writing: Practical and ethical considerations.

Generative artificial intelligence (AI) is transforming scientific communication in health, offering...

Growth curve models for weight among children up to 2 years: a scoping review.

OBJECTIVE: The aim of this scoping review was to systematically identify and map the literature on s...

Using Neural Networks to Complement Oximetry in Infant Obstructive Sleep Apnea: Working on Baby Steps.

Deep learning improves image quality in motion-robust and sedation-free pediatric brain MRI.

OBJECTIVES: Motion and limited compliance compromise diagnostic MR image quality, particularly in pe...

Individualized treatment strategies and long-term prognosis of congenital hydrocephalus: an integrated analysis based on multicenter retrospective data and machine learning.

INTRODUCTION: Hydrocephalus is a common pediatric neurological disorder characterized by abnormal he...

Comparing Risk Profiles of Nicotine Pouch and Smokeless Tobacco Use in U.S. Adolescents: A Machine Learning Analysis.

Background: This study identified and compared the risk profiles associated with nicotine pouch (NP)...

Exploring the Ethical and Practical Considerations of Artificial Intelligence in Real-World Health Care Settings: Stakeholder Focus Group Study.

BACKGROUND: Artificial intelligence (AI) technologies continue to transform how we research human di...