International journal of paediatric dentistry
May 9, 2024
BACKGROUND: Changes in healthy and inflamed pulp on periapical radiographs are traditionally so subtle that they may be imperceptible to human experts, limiting its potential use as an adjunct clinical diagnostic feature.
BACKGROUND: Observation of child behaviour provides valuable clinical information but often requires rigorous, tedious, repetitive and time expensive protocols. For this reason, tests requiring significant time for administration and rating are rarel...
Journal of experimental child psychology
May 9, 2024
This study examined children's beliefs about a humanoid robot by examining their behavioral and verbal responses. We investigated whether 3- and 5-year-old children would treat the humanoid robot gently along with other objects and tools with and wit...
The Pediatric infectious disease journal
May 8, 2024
BACKGROUND: Early identification of high-risk groups of children with sepsis is beneficial to reduce sepsis mortality. This article used artificial intelligence (AI) technology to predict the risk of death effectively and quickly in children with sep...
OBJECTIVE: One of the main causes of death worldwide among young people are car crashes, and most of these fatalities occur to children who are seated in the front passenger seat and who, at the time of an accident, receive a direct impact from the a...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
May 7, 2024
Analyzing the basal ganglia following an early brain lesion is crucial due to their noteworthy role in sensory-motor functions. However, the segmentation of these subcortical structures on MRI is challenging in children and is further complicated by ...
PURPOSE: To develop a deep learning (DL) model for classifying histological types of primary bone tumors (PBTs) using radiographs and evaluate its clinical utility in assisting radiologists.
OBJECTIVE: The search for other indicators to assess the weight status of individuals is important as it may provide more accurate information and assist in personalized medicine.This work is aimed to develop a machine learning predictions of weigh s...
PURPOSE: Early onset scoliosis (EOS) patient diversity makes outcome prediction challenging. Machine learning offers an innovative approach to analyze patient data and predict results, including LOS in pediatric spinal deformity surgery.
AIM: This study aimed to develop highly precise radiomics and deep learning models to accurately detect acute lymphoblastic leukemia (ALL) using a T1WI image.