Pediatrics

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 of patients with adolescent idiopathic scoliosis (AIS). The Lenke classification system plays a pivotal role in determining the appropriate fusion levels for treatment planning. However, the presence of interobserver variability and time-intensive procedures presents challenges for clinicians. The p...

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 mortality, emphasizing the crucial need for its early diagnosis. Ultrasound is the primary imaging modality for prenatal CHD screening. As a complement to the four-chamber view, the three-vessel view (3VV) plays a vital role in detecting anomalies in the great vessels. However, the interpretation of feta...

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 technology for precise digital diagnostic analysis....

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 visualize segmentation on emergent CT scans. The model'...

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 bronchopulmonary dysplasia (BPD) using a set of machin...

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, the outbreak of COVID-19 has affected the health, ...

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 truly diagnose children with adolescent idiopathic sc...

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 the miniaturization of sensors and platforms, contem...

Radiomics and artificial intelligence applications in pediatric brain tumors.

BACKGROUND: The study of central nervous system (CNS) tumors is particularly relevant in the pediatric population because of their relatively high fre...

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 programs at neonatal intensive care unit (NICU) dis...

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 providers and researchers for their potential to im...

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 world, and the health care sector has not been immune...

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 management and reclamation. Although previous studies have...

Optimal use of β-lactams in neonates: machine learning-based clinical decision support system.

BACKGROUND: Accurate prediction of the optimal dose for β-lactam antibiotics in neonatal sepsis is challenging. We aimed to evaluate whether a reliabl...

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 factors affecting the treatment plan and its outcome. ...

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 application background. As an AI decision support system ...

Improving data participation for the development of artificial intelligence in dermatology.

Artificial intelligence (AI) has the potential to significantly impact many aspects of dermatology. The visual nature of dermatology lends itself to i...

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 (DL) applications for musculoskeletal disease detect...

Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data.

Despite the remarkable advances in cancer diagnosis, treatment, and management over the past decade, malignant tumors remain a major public health pro...

Inductive reasoning with type-constrained encoding for emerging entities.

Knowledge graph reasoning, vital for addressing incompleteness and supporting applications, faces challenges with the continuous growth of graphs. To ...