AIMC Topic: Child, Preschool

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Children's animistic beliefs toward a humanoid robot and other objects.

Journal of experimental child psychology
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...

Establishment and Verification of an Artificial Intelligence Prediction Model for Children With Sepsis.

The Pediatric infectious disease journal
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...

Child face detection on front passenger seat through deep learning.

Traffic injury prevention
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...

GNN-based structural information to improve DNN-based basal ganglia segmentation in children following early brain lesion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
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 ...

The role of various physiological and bioelectrical parameters for estimating the weight status in infants and juveniles cohort from the Southern Cuba region: a machine learning study.

BMC pediatrics
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...

Utilizing a comprehensive machine learning approach to identify patients at high risk for extended length of stay following spinal deformity surgery in pediatric patients with early onset scoliosis.

Spine deformity
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.

Development of an immunoinflammatory indicator-related dynamic nomogram based on machine learning for the prediction of intravenous immunoglobulin-resistant Kawasaki disease patients.

International immunopharmacology
BACKGROUND: Approximately 10-20% of Kawasaki disease (KD) patients suffer from intravenous immunoglobulin (IVIG) resistance, placing them at higher risk of developing coronary artery aneurysms. Therefore, we aimed to construct an IVIG resistance pred...

Image segmentation of impacted mesiodens using deep learning.

The Journal of clinical pediatric dentistry
This study aimed to evaluate the performance of deep learning algorithms for the classification and segmentation of impacted mesiodens in pediatric panoramic radiographs. A total of 850 panoramic radiographs of pediatric patients (aged 3-9 years) was...