Pediatrics

Machine learning to infer neurocognitive testing scores among adolescents and young adults with congenital heart disease.

BACKGROUND: Congenital heart disease (CHD) affects about 1% of births and is linked to differences i...

Evaluation and application of electrocardiographic age model for children.

ECG-age, derived from ECG signals using deep neural networks (DNNs), correlates with health status b...

Offline AI-assisted fundus imaging for preliminary screening of childhood glaucoma.

PURPOSE: To evaluate the feasibility and performance of AI-assisted portable fundus photography in c...

Microvascular phenotypes in pediatric sepsis identified by machine learning: prognostic implications for organ dysfunction and mortality.

Breaking the 2-nm Barrier in Hard Disk Drives Using Monolayer Amorphous Carbon Overcoats.

The rapid growth of artificial intelligence (AI) has increased the demand for large-scale data stora...

Exploring Clinician Perspectives on Artificial Intelligence in Primary Care: Qualitative Systematic Review and Meta-Synthesis.

BACKGROUND: Recent advances have highlighted the potential of artificial intelligence (AI) systems t...

Meconium metabolomic profiling dysregulation and neonatal brain injury in selective fetal growth restriction.

BACKGROUND: Meconium serves as a valuable biological matrix for characterizing fetal metabolic signa...

A comparative evaluation of two large language models in pediatric dentistry.

A methodological comparative analysis of monetary policy and trade openness on economic growth in West Africa: Does language play a role?

The study examines the effect of monetary policy and trade openness on economic growth in the ECOWAS...

Impacts of delayed influenza vaccination on clinical outcomes in ICU-admitted patients with influenza: A retrospective cohort study.

BACKGROUND: Influenza vaccination is an effective measure for reducing the risk of severe influenza ...

Understanding public perceptions of cultural ecosystem services in urban coastal wetland ecological restoration areas: A social media-based large language model approach.

Understanding public perceptions of cultural ecosystem services (CES) in urban coastal wetland ecolo...

Integrated single-cell analyses of affinity-tested B cells enable the identification of a gene signature to predict antibody affinity.

Advancements in single-cell technologies and deep sequencing have expanded the B cell repertoire ava...

Patients' Attitudes and Beliefs Toward Artificial Intelligence Use in Cancer Care: Cross-Sectional Survey Study.

BACKGROUND: Artificial intelligence (AI) is being rapidly integrated into oncologic care, yet little...

HappyMums mobile application study protocol: use of a smartphone application to gather data predictive of antenatal depression.

INTRODUCTION: Mobile health (mHealth) technologies have become increasingly popular for monitoring m...

Deep neural network-based analysis of voice biomarkers for monitoring treatment response in adolescent major depressive disorder.

BACKGROUND: In adolescents, identifying objective biomarkers for treatment response is crucial for t...

Utilizing optical coherence tomography and machine learning to identify vision abnormalities in pediatric neurofibromatosis type 1 patients.

Neurofibromatosis type 1 (NF-1) is a genetic disorder associated with a high risk of vision loss in ...

Validation of an AI model for pediatric myelin maturation age assessment and benefits for junior radiologists.

Clinical Profile of Neurosurgical Consultations from the Emergency Department : A Retrospective Analysis.

OBJECTIVE: This study aimed to retrospectively analyze consultations requested from the emergency de...

Multiple weak biases support adaptive choices without prior experience: a self-supervised strategy.

From social interaction to foraging, the survival of newborn animals depends on their ability to mak...

3D-QALAS synthetic MRI with Zero-DeepSub in children: initial experience including post-contrast imaging feasibility.

BACKGROUND: Magnetic resonance imaging (MRI) in children requires multiple sequences, leading to len...

Prediction of Fontan failure and correlates of Fontan-associated liver disease severity using machine learning and radiomic features from multi-parametric abdominal MRI.

BACKGROUND: Fontan-associated liver disease (FALD) is associated with morbidity and mortality in pat...