Pediatrics

Securing Federated Learning With Blockchain in the Medical Field: Systematic Literature Review.

BACKGROUND: The exponential growth of medical data and advancements in artificial intelligence (AI) have accelerated the development of data-driven health care. However, the secure and efficient sharing of sensitive medical data across institutions remains a major challenge due to privacy concerns, data silos, and regulatory restrictions. Traditional centralized systems are prone to data breaches ...

Pneumonia detection from enhanced chest X-Ray images based on Double SGAN model.

Medical imaging plays a crucial role in clinical diagnosis, however, deep learning models often struggle with imbalanced datasets, which has a negative impact on the accuracy and robustness of pneumonia image classification. This study proposes a deep learning based diagnostic system for pneumonia detection using chest X-ray images. Using the pneumonia MNIST dataset, including pediatric lung image...

Ultra-Fast Sub-Minute Brain MRI with Deep-Learning-reconstruction for Anesthesia-Free Emergency Imaging in Children.

PURPOSE: As MRI frequently requires general anesthesia in pediatric patients, there is an undersupply in clinical routine. This may result in delayed ...

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, is a major point of failure in human development, ...

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 interpretability and reliability are critical. Most existin...

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 by measuring key physiological variables including ...

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 categorize vaccine-related myths reported by healthcare p...

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 opacity projected shadow (LOPS) on ultra-widefield ...

Artificial Intelligence in African Cardiovascular Care: Opportunities, Challenges, and Pathways to Improved Outcomes.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality in Africa, accounting for over 1 million deaths annually. As CVD preva...

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 capacity of screening programs has outpaced the a...

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 research exists examining the psychological impacts of v...

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

Ophthalmology significantly contributes to the healthcare sector's carbon footprint. Despite recent increases in sustainability research in ophthalmol...

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 understanding brain development. However, assessing my...

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 critical. While school-based mindfulness training (SBMT...

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 simulation remains challenging owing to the need for ...

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 worldwide. It is imperative to understand the service qu...

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 information is concerning, as they were not originally...

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 deteriorates during prolonged storage, impacting consumer ...

Abnormal Lipid Signaling Characterizes Diastolic Dysfunction in Pediatric Cardiomyopathy.

Pediatric cardiomyopathy is a major cause of diastolic heart failure; yet, its mechanisms remain unclear. Global myocardial transcriptomic and blood l...