Pediatrics

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

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Video Clip Extraction From Fetal Ultrasound Scans Using Artificial Intelligence to Allow Remote Second Expert Review for Congenital Heart Disease.

OBJECTIVE: To use artificial intelligence (AI) to automatically extract video clips of the fetal hea...

Initializing a Public Repository for Hosting Benchmark Datasets to Facilitate Machine Learning Model Development in Food Safety.

While there is clear potential for artificial intelligence (AI) and machine learning (ML) models to ...

An Ontology for Digital Medicine Outcomes: Development of the Digital Medicine Outcomes Value Set (DOVeS).

BACKGROUND: Over the last 10-15 years, US health care and the practice of medicine itself have been ...

Artificial intelligence in mental health care: a systematic review of diagnosis, monitoring, and intervention applications.

Artificial intelligence (AI) has been recently applied to different mental health illnesses and heal...

Machine Learning-Based Pediatric Early Warning Score: Patient Outcomes in a Pre- Versus Post-Implementation Study, 2019-2023.

OBJECTIVES: To describe the deployment of pediatric Calculated Assessment of Risk and Triage (pCART)...

Deep learning: A game changer in drug design and development.

The lengthy and costly drug discovery process is transformed by deep learning, a subfield of artific...

A living scoping review and online repository of artificial intelligence models in pediatric urology: Results from the AI-PEDURO collaborative.

INTRODUCTION: Artificial intelligence (AI) is increasingly being applied across pediatric urology. W...

Association between deep learning radiomics based on placental MRI and preeclampsia with fetal growth restriction: A multicenter study.

PURPOSE: Preeclampsia (PE) is associated with placental insufficiency and could lead to adverse preg...

Artificial Intelligence in Pediatric Endocrinology.

The rapid technological progress over the last couple of decades has paved the way for innovative me...

Development of an mPBPK machine learning framework for early target pharmacology assessment of biotherapeutics.

Development of antibodies often begins with the assessment and optimization of their physicochemical...

Human mobility is well described by closed-form gravity-like models learned automatically from data.

Modeling human mobility is critical to address questions in urban planning, sustainability, public h...

Inspired by the growth behavior of plants: biomimetic soft robots that just meet the requirements of use.

Soft robots are usually manufactured using the pouring method and can only be configured with a fixe...

Interoperable Models for Identifying Critically Ill Children at Risk of Neurologic Morbidity.

IMPORTANCE: Decreasing mortality in the field of pediatric critical care medicine has shifted practi...

Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling.

BACKGROUND: Older persons comprise most traumatic brain injury (TBI)-related hospitalizations and de...

Harmonizing flows: Leveraging normalizing flows for unsupervised and source-free MRI harmonization.

Lack of standardization and various intrinsic parameters for magnetic resonance (MR) image acquisiti...

Development and validation of fully automated robust deep learning models for multi-organ segmentation from whole-body CT images.

PURPOSE: This study aimed to develop a deep-learning framework to generate multi-organ masks from CT...

Navigating the future of pediatric cardiovascular surgery: Insights and innovation powered by Chat Generative Pre-Trained Transformer (ChatGPT).

INTRODUCTION: Interdisciplinary consultations are essential to decision-making for patients with con...

Artificial intelligence in surgery: evolution, trends, and future directions.

Artificial intelligence (AI) is significantly transforming surgery by enhancing precision, decision-...

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