Pediatrics

Automated measurements of interscrew angles in vertebral body tethering patients with deep learning.

BACKGROUND CONTEXT: Vertebral body tethering is the most popular nonfusion treatment for adolescent ...

Clinical Uptake of Pediatric Exoskeletons: Pilot Study Using the Consolidated Framework for Implementation Research.

OBJECTIVE: While the design and clinical evidence base of robot-assisted gait training devices has b...

Walking and falling: Using robot simulations to model the role of errors in infant walking.

What is the optimal penalty for errors in infant skill learning? Behavioral analyses indicate that e...

Centering Public Perceptions on Translating AI Into Clinical Practice: Patient and Public Involvement and Engagement Consultation Focus Group Study.

BACKGROUND: Artificial intelligence (AI) is widely considered to be the new technical advancement ca...

Embryonic cranial cartilage defects in the Fgfr3 mouse model of achondroplasia.

Achondroplasia, the most common chondrodysplasia in humans, is caused by one of two gain of function...

Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project.

This review paper presents the practical development of imaging biomarkers in the scope of the PRIMA...

Analysis of Prospective Genetic Indicators for Prenatal Exposure to Arsenic in Newborn Cord Blood of Using Machine Learning.

Using a machine learning methods, we aim to find biological effect biomarkers of prenatal arsenic ex...

Artificial intelligence to identify fractures on pediatric and young adult upper extremity radiographs.

BACKGROUND: Pediatric fractures are challenging to identify given the different response of the pedi...

Using Artificial Intelligence to Detect Congenital Anomalies.

Predicting 'Brainage' in late childhood to adolescence (6-17yrs) using structural MRI, morphometric similarity, and machine learning.

Brain development is regularly studied using structural MRI. Recently, studies have used a combinati...

Cost-effectiveness analysis of robot-assisted laparoscopic surgery for complex pediatric surgical conditions.

BACKGROUND: Robotics has been used safely and successfully in a variety of adult surgeries and is gr...

A deep sift convolutional neural networks for total brain volume estimation from 3D ultrasound images.

Preterm infants are a highly vulnerable population. The total brain volume (TBV) of these infants ca...

Quantitative assessment of transforming growth factor-β1 release from dentin matrix upon conditioning with ethylene diamine tetra-acetate, doxycycline hydrochloride, and propolis: An study.

BACKGROUND: Transforming growth factor-beta 1 (TGF-β1) is a key morphogen in regenerative endodontic...

Artificial Intelligence in Pediatric Urology.

Application of artificial intelligence (AI) is one of the hottest topics in medicine. Unlike traditi...

Using artificial intelligence algorithms to predict the overall survival of hemodialysis patients during the COVID-19 pandemic: A prospective cohort study.

BACKGROUND: Hemodialysis (HD) patients are a vulnerable population at high risk for severe complicat...

An interpretable deep learning model for time-series electronic health records: Case study of delirium prediction in critical care.

Deep Learning (DL) models have received increasing attention in the clinical setting, particularly i...

Capturing Emerging Experiential Knowledge for Vaccination Guidelines Through Natural Language Processing: Proof-of-Concept Study.

BACKGROUND: Experience-based knowledge and value considerations of health professionals, citizens, a...

Navigating the AI Revolution: The Case for Precise Regulation in Health Care.

Health care is undergoing a profound transformation through the integration of artificial intelligen...

Testing the performance, adequacy, and applicability of an artificial intelligence model for pediatric pneumonia diagnosis.

BACKGROUND: Community-acquired Pneumonia (CAP) is a common childhood infectious disease. Deep learni...

A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data.

With the advances in technology and data science, machine learning (ML) is being rapidly adopted by ...

Early Experience With Pediatric Single-port Robotic Pyeloplasty Compared to Multiport Robotic Cohorts. Reply.