Pediatrics

Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies.

A recent experiment probed how purposeful action emerges in early life by manipulating infants' func...

Evaluation of 3D T1-weighted spoiled gradient echo MR image quality using artificial intelligence image reconstruction techniques in the pediatric brain.

PURPOSE: To assess image quality and diagnostic confidence of 3D T1-weighted spoiled gradient echo (...

Artificial intelligence chatbots: Are they a reliable source for patients and families in pediatric neuro-oncology?

Automatic semantic segmentation of EHG recordings by deep learning: An approach to a screening tool for use in clinical practice.

BACKGROUND AND OBJECTIVE: Preterm delivery is an important factor in the disease burden of the newbo...

Concepts for the Development of Person-Centered, Digitally Enabled, Artificial Intelligence-Assisted ARIA Care Pathways (ARIA 2024).

The traditional healthcare model is focused on diseases (medicine and natural science) and does not ...

Validation of Artificial Intelligence in the Classification of Adolescent Idiopathic Scoliosis and the Compairment to Clinical Manual Handling.

OBJECTIVE: The accurate measurement of Cobb angles is crucial for the effective clinical management ...

A Coarse-Fine Collaborative Learning Model for Three Vessel Segmentation in Fetal Cardiac Ultrasound Images.

Congenital heart disease (CHD) is the most frequent birth defect and a leading cause of infant morta...

Adaptive Multi-Dimensional Weighted Network With Category-Aware Contrastive Learning for Fine-Grained Hand Bone Segmentation.

Accurately delineating and categorizing individual hand bones in 3D ultrasound (US) is a promising t...

Artificial Intelligence Application in Skull Bone Fracture with Segmentation Approach.

This study aims to evaluate an AI model designed to automatically classify skull fractures and visua...

Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia.

AIM: To develop a decision-support tool for predicting extubation failure (EF) in neonates with bron...

Modeling and control of COVID-19 disease using deep reinforcement learning method.

The prevalence of epidemics has been studied by researchers in various fields. In the last 2 years, ...

Using machine learning to automatically measure kyphotic and lordotic angle measurements on radiographs for children with adolescent idiopathic scoliosis.

Measuring the kyphotic angle (KA) and lordotic angle (LA) on lateral radiographs is important to tru...

Deep learning-based prediction of plant height and crown area of vegetable crops using LiDAR point cloud.

Remote sensing has been increasingly used in precision agriculture. Buoyed by the developments in th...

Radiomics and artificial intelligence applications in pediatric brain tumors.

BACKGROUND: The study of central nervous system (CNS) tumors is particularly relevant in the pediatr...

Machine learning risk stratification for high-risk infant follow-up of term and late preterm infants.

BACKGROUND: Term and late preterm infants are not routinely referred to high-risk infant follow-up p...

Making sense of artificial intelligence and large language models-including ChatGPT-in pediatric hematology/oncology.

ChatGPT and other artificial intelligence (AI) systems have captivated the attention of healthcare p...

Legal implications of artificial intelligence in health care.

The last few years have seen a boom in the popularity of artificial intelligence (AI) around the wor...

Improved classification of soil As contamination at continental scale: Resolving class imbalances using machine learning approach.

The identification of arsenic (As)-contaminated areas is an important prerequisite for soil manageme...

Estimating mandibular growth stage based on cervical vertebral maturation in lateral cephalometric radiographs using artificial intelligence.

INTRODUCTION: Determining the right time for orthodontic treatment is one of the most important fact...

Constructing and implementing a performance evaluation indicator set for artificial intelligence decision support systems in pediatric outpatient clinics: an observational study.

Artificial intelligence (AI) decision support systems in pediatric healthcare have a complex applica...

Artificial intelligence in musculoskeletal imaging: realistic clinical applications in the next decade.

This article will provide a perspective review of the most extensively investigated deep learning (D...