Pediatrics

FATE-MAP predicts teratogenicity and human gastrulation failure modes by integrating deep learning and mechanistic modeling.

Gastrulation, a critical developmental stage involving germ layer specification and axes formation, ...

Robust and interpretable unit level causal inference in neural networks for pediatric myopia.

Understanding causal mechanisms in deep learning is essential for clinical adoption, where interpret...

Predicting cardiopulmonary exercise testing outcomes in congenital heart disease through multimodal data integration and geometric learning.

Cardiopulmonary exercise testing (CPET) provides a comprehensive assessment of functional capacity b...

Perception of vaccine myths in daily clinical practice: A survey of healthcare professionals.

Introduction. Misinformation is a barrier to immunization. The objective was to describe and categor...

Predicting Visual Outcomes in Congenital Posterior Lens Opacities: A Deep Learning Model Using Ultra-Widefield Fundus Images.

PURPOSE: To develop and validate a deep learning (DL) model for the automatic segmentation of lens o...

Landmark-based deep learning for radiographic screening for developmental dysplasia of the hip in infants: Development and external evaluation with IHDI-guided triage.

BACKGROUND: In Japan, secondary screening for developmental hip dysplasia has expanded. However, the...

Metadata Resolution Spoofing for Pediatric Application of Adult-Trained Deep Learning Models for Pancreas Segmentation on CT.

Filtering Trust: Disclosing the Role of Artificial Intelligence Decreases Trust in Technology, but Does Not Prevent Harm to Body Image After Viewing AI-Generated Content.

OBJECTIVES: Despite the rapid growth of generative artificial intelligence (AI), virtually no resear...

Sustainable Ophthalmology Applications: From the Perspective of Strabismus and Pediatric Ophthalmology.

Ophthalmology significantly contributes to the healthcare sector's carbon footprint. Despite recent ...

Dual-Modal Deep Learning with In-Domain Training and Attention for Infant Brain Myelination Prediction.

Myelin plays a critical role in the central nervous system, and its maturation is essential for unde...

Predicting Adolescent Response to School-Based Mindfulness: A Secondary Analysis of the MYRIAD Trial.

IMPORTANCE: Depression most commonly first emerges during adolescence, making early prevention criti...

Ready-to-Use Polymerization Simulations Combining Universal Machine Learning Interatomic Potential with Time-Dependent Bond Boosting for Polymer and Interface Design.

Although polymerization and curing reactions govern the performance of advanced materials, their sim...

Developing a Service Quality Index System for AI Health Care Chatbots: Mixed Methods Study.

BACKGROUND: Artificial intelligence (AI) health care chatbots are gaining widespread adoption worldw...

Examining Artificial Intelligence Chatbots' Responses in Providing Human Papillomavirus Vaccine Information for Young Adults: Qualitative Content Analysis.

BACKGROUND: The growing use of artificial intelligence (AI) chatbots for seeking health-related info...

Machine learning-driven flavoromics: Decoding stage-specific volatile compound dynamics and sensory deterioration in stored infant formula.

Infant formula (IF) is a vital nutritional source for infants. However, its sensory quality deterior...

Abnormal Lipid Signaling Characterizes Diastolic Dysfunction in Pediatric Cardiomyopathy.

Pediatric cardiomyopathy is a major cause of diastolic heart failure; yet, its mechanisms remain unc...

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 t...

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 car...

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-ho...

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 challen...