Pediatrics

Predicting mycophenolic acid exposure in pediatric lupus nephritis: a real-world study across three clinical scenarios.

OBJECTIVES: Childhood-onset systemic lupus erythematosus (cSLE) with lupus nephritis (LN) presents therapeutic challenges due to complex mycophenolic acid (MPA) pharmacokinetics. This study developed machine learning (ML)-based models to predict MPA area under the concentration-time curve (MPA-AUC) across three scenarios: determining therapeutic window attainment, precise AUC estimation, and forec...

Artificial intelligence meets point-of-care ultrasound: implications for pediatric emergency and critical care.

PURPOSE OF REVIEW: Artificial intelligence has been integrated in nearly all aspects of clinical care to improve patient outcomes, augment human capabilities and improve efficiency. Particularly in the field of radiology and medical imaging, artificial intelligence could revolutionize how care is delivered. In this review, we review the recent literature and provide an assessment of the advantages...

Barriers to implementing AI in pediatric cancer imaging.

Gross motor performance of infants with an at-home wearable measurement and the Alberta Infant Motor Scale: A concurrent validity study.

AIM: To evaluate the concurrent validity of assessing infants' gross motor performance with an at-home wearable measurement versus the Alberta Infant ...

Machine Learning Methods to Identify Pediatric Shunt Malfunction in the Acute Care Setting and the Development of ShuntGPT.

BACKGROUND AND OBJECTIVES: Identifying predictors of shunt failure in acute care settings is challenging. Previous studies largely rely on traditional...

Epidemiological Trajectories and Quality of Care Disparities of MASLD in Asia, 1990-2023.

BACKGROUND: To characterize temporal and geographic patterns of metabolic dysfunction-associated steatotic liver disease (MASLD) across Asia from 1990...

Neonatal jaundice detection using a vision transformer-based deep learning model.

Leveraging Machine Learning to Uncover Ethnic-Specific Predictors of Maternal Postpartum Depression.

Maternal postpartum depression (PPD) is a significant mental health issue that affects over 15% of mothers, with adverse effects on their children. Et...

Corrigendum to "Deep learning in fetal, infant, and toddler neuroimaging research"[Dev. Cognit. Neurosci. (2026), 101680].

Peripheral Retinal Vessel Density in Children and Adolescents with Myopia: A Deep Learning Assessment.

INTRODUCTION: This study investigated the effect of axial length (AL) on peripheral retinal vessel density in children and adolescents and assessed wh...

Generative Artificial Intelligence in Neonatal Diagnostic Reasoning: Promise, Prudence, and the Path Ahead.

Development, Validation, and Comparison of Machine Learning Models for Predicting Pediatric Surgical Site Infections Using the NSQIP-P Database.

BACKGROUND: Surgical site infections (SSIs) cause substantial postoperative morbidity in children. Despite being largely preventable, SSI rates have c...

Neuroprognostication via Radiomics and Machine Learning Following Neonatal Hypoxic-Ischemic Insult.

OBJECTIVE: To produce objective predictions of neurodevelopmental outcomes after perinatal hypoxic-ischemic insult for the full spectrum of severity o...

Expanding the horizon of oculomics: A narrative review on the emerging roles of the anterior segment and mobile health.

Oculomics uses the eye to gain insights into systemic health. Although initially focused on retinal imaging, oculomics now studies various ocular sign...

Minor salivary gland biopsy in Sjogren's disease: a diagnostic and prognostic tool toward precision medicine.

Minor salivary gland biopsy occupies a distinctive position in the evaluation of Sjögren disease (SjD), offering diagnostic and prognostic insights th...

Deep learning-based cerebellar segmentation on T2-weighted fluid-attenuated inversion recovery magnetic resonance imaging for detecting cerebellar hypoplasia/atrophy in infants.

BACKGROUND: Accurate measurement of cerebellar volume is crucial for diagnosing cerebellar atrophy or hypoplasia in infants. Although deep learning ha...

A modern radiologist's guide to artificial intelligence.

Artificial intelligence (AI) has the potential to disrupt many fields, and radiology is no exception. The applications of AI in this field go beyond a...

ContraIndicator: A Natural Language Processing-Based Approach to Potential Drug-Drug Interaction Detection in Pediatric Intensive Care.

BACKGROUND AND OBJECTIVES: The intricate nature of pediatric patients' physiology and the frequent administration of multiple medications in pediatric...

Whole-body magnetic resonance imaging in rheumatology: advancements, key applications and future perspectives.

Whole-body magnetic resonance imaging (WB-MRI) is widely used in rheumatology to assess peripheral and axial joints and entheses throughout the body. ...

Overview of a User-Centered, Mixed-Methods Process for Designing Interconnected and Focused Mobile Applications on Patient Care Environment (InterFACE): Augmented-Reality Decision Support System for Pediatric Resuscitation.

BACKGROUND: Pediatric cardiopulmonary resuscitation (CPR) is a highly complex and time-critical process that demands precise team coordination and str...