Artificial intelligence (AI) systems have increasingly achieved expert-level performance in medical imaging applications. However, there is growing concern that such AI systems may reflect and amplify human bias, and reduce the quality of their perfo...
It is challenging to extract the brain region from T2-weighted magnetic resonance infant brain images because conventional brain segmentation algorithms are generally optimized for adult brain images, which have different spatial resolution, dynamic ...
In view of the growth of clinical risk prediction models using genetic data, there is an increasing need for studies that use appropriate methods to select the optimum number of features from a large number of genetic variants with a high degree of r...
BACKGROUND: Early and accurate radiographic diagnosis is required for the management of children with radio-opaque esophageal foreign bodies. Button batteries are some of the most dangerous esophageal foreign bodies and coins are among the most commo...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 26, 2021
Assessment of spontaneous movements can predict the long-term developmental disorders in high-risk infants. In order to develop algorithms for automated prediction of later disorders, highly precise localization of segments and joints by infant pose ...
Diagnostic and interventional imaging
Nov 19, 2021
PURPOSE: The purpose of this study was to conduct an external validation of a fracture assessment deep learning algorithm (Rayvolve®) using digital radiographs from a real-life cohort of children presenting routinely to the emergency room.
Malformations of cortical development (MCD) comprise a broad spectrum of structural brain lesions frequently associated with epilepsy. Disease definition and diagnosis remain challenging and are often prone to arbitrary judgment. Molecular classifica...
The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
Nov 17, 2021
OBJECTIVE: Several severity metrics have been developed for metopic craniosynostosis, including a recent machine learning-derived algorithm. This study assessed the diagnostic concordance between machine learning and previously published severity ind...
BACKGROUND: New technology attracts necessary concerns regarding safety and effectiveness, including the risk and circumstances of conversions. This study analyses our 11-year experience of conversions from a dedicated pediatric robot-assisted laparo...
OBJECTIVES: Medically minor but clinically important findings associated with physical child abuse, such as bruises in pre-mobile infants, may be identified by frontline clinicians yet the association of these injuries with child abuse is often not r...