Pediatrics

Latest AI and machine learning research in pediatrics for healthcare professionals.

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Comparative Accuracy of Generative Artificial Intelligence Platforms on Predoctoral Pediatric Dentistry Examination.

To determine the comparative accuracy of seven generative artificial intelligence (GenAI) platforms...

Accuracy of Artificial Intelligence in Making Diagnoses and Treatment Decisions in Pediatric Dentistry.

To assess the diagnostic and treatment decision-making accuracy of ChatGPT for various dental probl...

A Multianalyte Machine Learning Model to Detect Wrong Blood in Complete Blood Count Tube Errors in a Pediatric Setting.

BACKGROUND: Multianalyte machine learning (ML) models can potentially identify previously undetectab...

Electrocardiogram-based deep learning to predict mortality in paediatric and adult congenital heart disease.

BACKGROUND AND AIMS: Robust and convenient risk stratification of patients with paediatric and adult...

Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models.

The blood brain barrier (BBB) is an endothelial-derived structure which restricts the movement of ce...

Towards artificial intelligence application in pain medicine.

Pain is a complex, multidimensional experience involving significant challenges in both diagnosis an...

A Tutorial and Use Case Example of the eXtreme Gradient Boosting (XGBoost) Artificial Intelligence Algorithm for Drug Development Applications.

Approaches to artificial intelligence and machine learning (AI/ML) continue to advance in the field ...

Bridging the Gap in Neonatal Care: Evaluating AI Chatbots for Chronic Neonatal Lung Disease and Home Oxygen Therapy Management.

OBJECTIVE: To evaluate the accuracy and comprehensiveness of eight free, publicly available large la...

Machine Learning and Natural Language Processing to Improve Classification of Atrial Septal Defects in Electronic Health Records.

BACKGROUND: International Classification of Disease (ICD) codes can accurately identify patients wit...

Can GPTs Accelerate the Development of Intelligent Diagnosis and Treatment in Traditional Chinese Medicine? A Survey and Empirical Analysis.

Intelligent traditional Chinese medicine (TCM) is a key pathway toward the modernization and globali...

Development of secure infrastructure for advancing generative artificial intelligence research in healthcare at an academic medical center.

BACKGROUND: Generative AI, particularly large language models (LLMs), holds great potential for impr...

AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation.

The primary practice of healthcare artificial intelligence (AI) starts with model development, often...

AI for Corneal Imaging: How Will This Help Us Take Care of Our Patients?

As artificial intelligence continues to evolve at a rapid pace, there is growing enthusiasm surround...

Advanced Artificial-Intelligence-Based Jiang Formula for Intraocular Lens Power in Congenital Ectopia Lentis.

PURPOSE: The purpose of this study was to develop an artificial intelligence (AI)-based intraocular ...

Assessing Completeness of Clinical Histories Accompanying Imaging Orders Using Adapted Open-Source and Closed-Source Large Language Models.

Background Incomplete clinical histories are a well-known problem in radiology. Previous dedicated q...

An artificial intelligence model for Lhermitte's sign in patients with pediatric-onset multiple sclerosis: A follow-up study.

BACKGROUND: Lhermitte's sign (LS) is an important clinical marker for patients with multiple scleros...

Exploring Ensemble Learning Techniques for Infant Mortality Prediction: A Technical Analysis of XGBoost Stacking AdaBoost and Bagging Models.

BACKGROUND: Infant mortality remains a critical public health issue, reflecting the overall health a...

Evaluation of Image Quality and Scan Time Efficiency in Accelerated 3D T1-Weighted Pediatric Brain MRI Using Deep Learning-Based Reconstruction.

OBJECTIVE: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pedi...

A Generalized Machine Learning Model for Identifying Congenital Heart Defects (CHDs) Using ICD Codes.

BACKGROUND: International Classification of Diseases (ICD) codes utilized for congenital heart defec...

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