Pediatrics

Pediatric Personalized Deep Learning Models for Segmentation of Hepatoblastoma at CT and MRI.

Purpose To evaluate the generalizability of adult-trained models for hepatoblastoma segmentation to pediatric patients and to develop two deep learning (DL) models, M P C T and M p M R I , specifically trained on pediatric contrast-enhanced CT and T2-weighted MRI scans, respectively. Materials and Methods Imaging data from the multicenter Children's Oncology Group AHEP0731 trial (NCT009804...

Maternal and Pediatric Precision in Therapeutic Knowledge Portal (MPRINT-KP): Landscape Analysis of Pharmacology Research in Maternal and Pediatric Patient Populations.

Pregnant women and children have been underrepresented in clinical studies due to ethical concerns and perceived vulnerabilities. This resulted in a significant gap in knowledge regarding the safety and efficacy of medications for these populations. Maternal and Pediatric PRecision In Therapeutics Knowledge Portal (MPRINT-KP) is designed to provide a comprehensive view of pharmacokinetic, pharmaco...

Fetal and neonatal alloimmune thrombocytopenia (FNAIT): From reactive transfusion to proactive prevention.

Fetal and neonatal alloimmune thrombocytopenia (FNAIT) is a major cause of severe thrombocytopenia, intracranial hemorrhage, and long-term neurologica...

Examining media coverage of ethical dimensions of advanced algorithmic technology.

The rapid integration of artificial intelligence, machine learning, and data science into daily life raises ethical concerns and stimulates discussion...

Evaluating Accuracy of ChatGPT-4o in Automated Carbohydrate Estimation From Images as a Self-Management Tool for Adolescents With Type 1 Diabetes.

INTRODUCTION: Type 1 diabetes mellitus (T1D) requires precise carbohydrate estimation to manage blood glucose and prevent chronic and acute complicati...

Stage-specific climate risks to winter wheat in China: actionable pathways to reconcile yield loss and protein gains.

As the global population continues to rise, ensuring nutrition security has become an increasingly critical concern. Climate change poses significant ...

Predicting mortality and short-term outcomes of continuous kidney replacement therapies in neonates and infants.

BACKGROUND: Continuous kidney replacement therapy (CKRT) has emerged as a valuable treatment option in critically ill neonates and infants with acute ...

The Future Was Yesterday. Artificial Intelligence in Newborn Medicine.

Liquid-Sequencer: A Lightweight Liquid Neural Network for Real-Time Fetal Congenital Heart Disease Diagnosis.

Congenital heart disease (CHD) is the leading cause of neonatal mortality worldwide, making early and accurate diagnosis crucial. In resource-constrai...

Machine learning estimation of FVIII pharmacokinetic parameters in Chinese children with severe Hemophilia A.

Hemophilia A is a rare inherited bleeding disorder typically managed with coagulation factor VIII (FVIII) replacement therapy. Designing personalized ...

Identification of key clinical features for pediatric respiratory syncytial virus infection using machine learning.

Effective communication training to support person- and whānau-centred care: what is needed and why isn't it happening?

AIMS: We sought to investigate the current state of education to support person- and whānau-centred care (PWCC) in our setting and to inform a new app...

A Preliminary Report: Screening Idiopathic Scoliosis (IS) With a Smartphone Application.

INTRODUCTION: Idiopathic scoliosis (IS) is a 3-dimensional spinal deformity that affects ∼3.1% of the population. Current strategies for IS screening ...

New treatments to rabies virus infections.

Rabies disease is the deadliest of all virus infections. Till now, vaccination is the most effective and reliable treatment for controlling rabies. Ho...

Integrating Multimodal Neuroimaging and Physical-Health Markers for Autism Spectrum Disorder in the ABCD Study.

BACKGROUND: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by diverse presentations, which complicates the ide...

Integrating Clinical Modeling and Machine Learning for Risk Assessment of Paracetamol and Other Nonsteroidal Anti-Inflammatory Drug Hypersensitivity in Children.

BACKGROUND: Nonsteroidal anti-inflammatory drug (NSAID) hypersensitivity is a common cause of drug-related reactions in children. Pre-test risk strati...

Artificial intelligence for personalized multiple micronutrient supplementation in maternal health.

Maternal undernutrition and micronutrient deficiencies remain pervasive, contributing to adverse pregnancy outcomes and long-term health risks for mot...

Clinically interpretable deep learning for pediatric dental age estimation with explainable AI.

Artificial Intelligence in Multiple Sclerosis: Possibilities in Radiological Diagnostics and Progression Assessment.

Multiple sclerosis (MS) is characterized by clinical and radiological heterogeneity. Recent refinements in the McDonald criteria and the integration o...

Plasma neurotransmitter-related metabolite alterations in adolescent major depressive disorder with and without psychotic features.

BACKGROUND: Whether adolescent major depressive disorder (MDD) with psychotic features has a distinct peripheral metabolite signature remains uncertai...