Pediatrics

Towards automated fetal brain biometry reporting for 3-dimensional T2-weighted 0.55-3T magnetic resonance imaging at 20-40 weeks gestational age range

The detailed assessment of fetal brain maturation and development involves morphological evaluation, gyration analysis, and reliable biometric measurements. Manual measurements on conventional 2-D magnetic resonance imaging (MRI) are affected by fetal motion and there is no clear consensus regarding definitions for brain biometric parameters and anatomical landmark placements, making consistent re...

InfEHR: Resolving Clinical Uncertainty through Deep Geometric Learning on Electronic Health Records

Electronic health records (EHRs) contain multimodal data that can inform diagnostic and prognostic clinical decisions but are often unsuited for advanced machine learning (ML)–based patient-specific analyses. ML models and clinical heuristics learn generalizable relationships from predefined factors, yet many patients may not benefit if those factors are missing in the EHR or differ—however subtly...

Plasma proteomics for novel biomarker discovery in childhood tuberculosis

Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of TB as a leading cause of death in children. Curren...

Data-driven consideration of genetic disorders for global genomic newborn screening programs

Over 30 international studies are exploring newborn sequencing (NBSeq) to expand the range of genetic disorders included in newborn screening. Substan...

Genetic variants risk assessment for Long QT Syndrome through machine learning and multielectrode array recordings

Long QT syndrome (LQTS) is a life-threatening genetic disorder characterized by prolonged QT intervals on electrocardiograms. Congenital forms are mos...

Development and Validation of an Artificial Intelligence Predictive Model to Accelerate Antibiotic Therapy for Critical Ill Children with Sepsis in the Pediatric ED with Pediatric ICU Disposition

Pediatric sepsis accounts for over 72,000 US hospitalizations annually with significant mortality and morbidity. Many pediatric hospitals struggle to ...

Artificial Intelligence (AI) Models for Cardiovascular Disease Risk Prediction in Primary and Ambulatory Care: A Scoping Review

Mortality from cardiovascular disease (CVD) has seen a dramatic increase over the past decades, which has led to a significant increase in the develop...

Expanding cholera serosurveillance to vaccinated populations

Mass oral cholera vaccination campaigns targeted at subnational areas with high incidence are central to global cholera elimination efforts. Serologic...

Pan-Omics Fusion and Machine Learning Unveil Congenital Tooth Agenesis-Ecto-mesodermal Diseases Link and Biomarker Discovery

Congenital tooth agenesis (CTA) is a common developmental anomaly with complex genetic and molecular mechanisms. Previous studies have primarily focus...

Mining Social Media Data for Influenza Vaccine Effectiveness Using a Large Language Model and Chain-of-Thought Prompting

Influenza vaccine effectiveness (VE) estimation plays a critical role in public health decision-making by quantifying the real-world impact of vaccina...

A Prospective Cohort Study to Develop Multi-Biomarkers Panel to Define Biological Ageing in Five Different Cohorts from Newborn to Oldest Adult: A Study Protocol

Age-associated disease management depends significantly on chronological age and macro-level clinical data sets. However, the biological age captures ...

Artificial Intelligence for Contextual Well-being: Protocol for an Exploratory Sequential Mixed Methods Study with Medical Students as a Social Microcosm

AI-powered conversational agents have proven effective in alleviating psychological distress, however, concerns about autonomy and authentic psycholog...

Training with synthetic data provides accurate and openly-available DNA methylation classifiers for developmental disorders and congenital anomalies via MethaDory

Multiple developmental and congenital disorders due to genetic variants or environmental exposures are associated with unique genome-wide alterations ...

Integrating Multilevel, Multidomain and Multimodal Neuroimaging Factors to Predict Early Alcohol Exposure Trajectories Using Explainable AI

Alcohol consumption tends to increase from childhood to adolescence, and risk factors at the individual, family, and environmental level (multilevel, ...

Development of a Machine Learning Tool for Home-Based Assessment of Periodontitis

According to an ADA report, approximately 15% of the US population requires dental care annually but does not receive it. Access to dental care, parti...

Polygenic Risk-Informed White Matter Integrity Improves Deep Learning-Based Prediction of Youth Depression

Early detection of youth depression is crucial, given its rising prevalence and long-term consequences. Although genetic factors contribute significan...

Unmet Needs in Acute Hepatic Porphyria Diagnosis: A Comparative Big Data Analysis of an AI-based Human-in-the-Loop Screening Versus Standard of Care

Acute Hepatic Porphyria (AHP) is a rare genetic disease characterized by unpredictable life-threatening attacks. There is no reliable biochemical scre...

Evaluating AI Reasoning Models in Pediatric Medicine: A Comparative Analysis of o3-mini and o3-mini-high

Artificial intelligence (AI) is increasingly playing a crucial role in modern medicine, particularly in clinical decision support. This study compares...

Towards Understanding Bipolar Disorder Through Social Media and Transformer Models: Challenges and Insights

Social media presents a promising avenue for monitoring mental health, yet detecting bipolar disorder (BD) remains significantly underexplored. The co...

Leveraging Unstructured Data in Electronic Health Records to Detect Adverse Events from Pediatric Drug Use - A Scoping Review

Adverse drug events (ADEs) in pediatric populations pose significant public health challenges, yet research on their detection and monitoring remains ...