Pediatrics

AI-Assisted Generation of Long-Term Follow-Up Recommendations for Survivors of Childhood Cancer and Hematopoietic Stem Cell Transplantation.

BACKGROUND: Survivors of childhood cancer and hematopoietic stem cell transplantation (HSCT) require...

Exploratory Implementation and Feasibility Report of CLASS (Clinical LLM Abstraction & Structuring System), A Large Language Model Pipeline for Extracting Unstructured Data From Clinical Notes.

Electronic medical records contain rich clinical detail, but much of it resides in unstructured note...

When Innovation Leaves People Behind: Reframing Accountability in Commercial Digital Health.

Digital technologies are increasingly integrated across health care systems; however, accumulating e...

Beyond efficiency: the AI-driven shift toward safer lipid nanoparticles for gene delivery.

Lipid nanoparticles (LNPs) have reshaped gene delivery, most notably through their pivotal role in m...

MEDAL: Sequential adapter learning for privacy-preserving multicenter clinical language models.

BACKGROUND: Scalable reasoning over clinical notes is a major goal in medical artificial intelligenc...

Artificial intelligence in orbital diseases: opportunities, challenges, and future horizons.

Orbital diseases-including thyroid eye disease, tumors, inflammation, fractures, vascular lesions, i...

Genomic Screening for Infants and Reproductive Adults.

Recent progress in genomic sequencing, bioinformatics, cloud computation, and artificial intelligenc...

Editorial for "Deep Learning Pipeline for Automatic Segmentation, Classification, and Molecular Subtyping of Three Pediatric Posterior Fossa Tumors Using T2-Weighted MRI".

Diagnostic accuracy of deep learning models for detecting wrist and distal forearm fractures in pediatric patients: A systematic review and meta-analysis.

PURPOSE: Pediatric wrist and distal forearm fractures are common but can be challenging to diagnose ...

Cost-utility and cost-effectiveness analysis of an AI-driven platform for standard postnatal care and breastfeeding: results from the COMLACT study.

OBJECTIVE: To assess whether an AI-driven technology for neonatal care is costeffective compared to ...

Development and Temporal External Validation of a Parsimonious, Interpretable Machine Learning Model for Predicting 6-Month Mortality in Long-Term Care Facilities: A Retrospective Cohort Study.

BACKGROUND: Early mortality after long-term care facility (LTCF) admission is common; yet, prognosti...

Dynamic Prediction of Day Mortality in Patients With Trauma Using a Hybrid Neural Network Model: Model Development and Evaluation Study.

BACKGROUND: The trajectory of a patient with trauma is often complex and nonlinear. Real-time estima...

Honest and Reliable Evaluation and Expert Equivalence Testing of Automated Neonatal Seizure Detection.

Reliable evaluation of machine learning models for neonatal EEG seizure detection is a prerequisite ...

Deterministic and ANN-based modelling of measles transmission using real epidemiological data.

This study aims to develop a nonlinear SVLIQR epidemic model to investigate measles transmission dyn...

MRI-based radiomics for prognosis of non-midline, pediatric high-grade gliomas.

PURPOSE: Non-midline, pediatric high-grade gliomas (HGG) represent one of the leading causes of canc...

Can Artificial Intelligence Deliver in Real-World Health Systems? Early Insights From Augmented Intelligence in Medicine and Healthcare Initiative's 5 Funded Projects.

INTRODUCTION: Artificial intelligence (AI) holds tremendous promise to improve clinical decision-mak...

Developmental cascades of daily living skills matter for adult outcomes in autism.

Daily living skills (DLS) predict adult success for autistic individuals. However, most research on ...

[Multicenter study of deep learning multitask model for predicting neoadjuvant chemotherapy response and event-free survival of pediatric head and neck rhabdomyosarcoma].

Objective: To investigate the value of a pretreatment magnetic resonance imaging (MRI)-based deep le...

Aberrant brain functional connectivity is associated with clinical symptoms in tourette syndrome: a triple network model perspective.

Tourette Syndrome (TS) is a neurodevelopmental disorder characterized by motor/vocal tics and premon...

[Digitalization and artificial intelligence in intensive care and emergency medicine : German Society for Internal Intensive Care and Emergency Medicine (DGIIN) position paper on targeted introduction].

In this position paper, the German Society for Internal Intensive Care and Emergency Medicine e. V. ...

Preparing for the future: A mixed methods study protocol on AI awareness and educational integration in Qatar's Primary Health Care Workforce.

BACKGROUND: Artificial intelligence (AI) is increasingly being integrated into healthcare systems, w...