Pediatrics

KD-SqueezeNet: an efficient deep learning strategy for the multi-task diagnosis of neonatal lung diseases.

BACKGROUND: The integration of deep learning in medical imaging has reached proficiency levels akin ...

Identifying microbial protease allergens through protein language model-guided homology.

Emerging research links the gut, skin, and oral microbiomes to allergies, with serine proteases (SPs...

Performance of Large Language Models Under Input Variability in Health Care Applications: Dataset Development and Experimental Evaluation.

BACKGROUND: Large language models (LLMs) are increasingly integrated into health care, where they co...

Experiences With Integrating Medical Terminologies Into User Interfaces for a Decision Support System for Primary Care: Conceptual and Development Study.

BACKGROUND: Clinical decision support systems (CDSSs) have shown promise in improving diagnosis in p...

A comprehensive UK crop yield dataset incorporating satellite, weather, and soil type information.

Agricultural research increasingly relies on data-driven approaches for crop yield prediction that c...

Machine Learning Prediction of Recurrence in Pediatric Thyroid Cancer: Malignant Endocrine Tumors Cohort Analysis Using XGBoost and SHAP.

CONTEXT: Pediatric differentiated thyroid carcinoma (DTC) often presents with advanced disease but g...

Modelling Follicular Growth During Ovarian Stimulation Using Agent-based Artificial Intelligence.

CONTEXT: Ovarian stimulation is a key step in medically assisted reproduction (MAR), whereby supraph...

Prediction of COVID-19 hospitalisation, ICU admission or death following ChAdOx1 vaccination using artificial intelligence: A clinical predictive model from the English RAVEN study.

OBJECTIVES: This study identifies predictors of severe COVID-19 following completion of two-dose pri...

Electroencephalography-Based Machine Learning Models for Predicting Ketogenic Diet Outcomes in Pediatric Drug-Resistant Epilepsy.

BACKGROUND: Ketogenic diet therapy (KDT) is an established treatment for drug-resistant epilepsy (DR...

Active surveillance methods to identify adverse events of special interest (AESIs) following vaccination against pandemic diseases: A scoping review.

INTRODUCTION: Active post-vaccination surveillance is vital for ensuring vaccine safety, particularl...

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) ...

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 stru...

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 undersuppl...

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...