Latest AI and machine learning research in pediatrics for healthcare professionals.
Plant ecological and evolutionary strategies are shaped by interactions between phylogenetic history and environmental constraints, resulting in leaf and stomatal traits. However, traditional trait-based and phylogenetic approaches often fail to fully explain biochemical mechanisms underlying ecological strategies, particularly for leaf and stomatal traits. Plant metabolomes integrate genetic, phy...
Background: Selective attention enables the prioritization of behaviorally relevant information in complex sensory environments. Despite substantial evidence for altered attention in autism spectrum disorder (ASD), the neurophysiological mechanisms underlying these differences remain poorly understood. Methods: Here, we integrate high-density electroencephalography (EEG), pupillometry, and behavio...
Vibrio natriegens is a halophilic, Gram-negative marine bacterium that is increasingly used in metabolic engineering applications due to its fast grow...
Adolescent psychopathology is partly rooted in measurable disruptions across key neural networks, yet the field still lacks an integrated, multimodal ...
Motivation: Quantitative assessment of neonatal internal capsule (IC) maturation remains largely reliant on qual- itative visual evaluation, limiting ...
Diastolic heart failure (HF) in primary cardiomyopathy is under-recognized and often diagnosed late, particularly in children. While recent studies ha...
Importance: Prenatal exposure to gestational diabetes mellitus (GDM) has been associated with adverse metabolic, neurodevelopmental, and psychiatric o...
Background & Aims: Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD) is the leading cause of chronic liver disease in children. However...
Adolescence is characterized by heightened reward sensitivity, novelty seeking, and risky decision-making. Prevailing neurodevelopmental frameworks ty...
Understanding and modeling how a single human genome concurrently encodes gene regulatory programs for thousands of cell types remains a central chall...
T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive pediatric malignancy characterized by complex heterogeneity across multiple molecular ...
Objective This study aimed to train and evaluate supervised machine learning algorithms using electronic health record (EHR) data to accurately estima...
Importance: Leukodystrophies are a heterogeneous group of genetic disorders affecting the white matter of the brain, often presenting with overlapping...
Surface-enhanced Raman scattering (SERS) nanotags provide highly sensitive platforms for in vitro diagnostics but often require complex, disease-speci...
Background and Purpose: Drug resistant epilepsy (DRE) affects approximately 15 million people worldwide, and surgery remains the only curative option....
Adolescence is a critical developmental window for the emergence of substance use and psychosis-spectrum symptoms, yet early risk for these outcomes r...
Antimicrobial stewardship (AMS) is critical in pediatric intensive care units (PICUs), where diagnostic uncertainty often drives broad-spectrum antibi...
Children with rare genetic diseases often exhibit distinctive facial phenotypes, yet developing computer vision systems for early diagnosis remains ch...
Ensuring global food security under rapid climate change demands accelerated genetic gain and breeding strategies that address complex Genotype-by-Env...
Adolescence is an important developmental period during which there are diverse changes in the brain and behavior. Goal-directed behaviors and the com...