AIMC Topic: Child, Preschool
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Child face detection on front passenger seat through deep learning.
Traffic injury prevention
May 8, 2024
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
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 ...
A radiograph-based deep learning model improves radiologists' performance for classification of histological types of primary bone tumors: A multicenter study.
European journal of radiology
May 7, 2024
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.
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
May 6, 2024
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
May 3, 2024
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.
Radiomics model and deep learning model based on T1WI image for acute lymphoblastic leukemia identification.
Clinical radiology
May 3, 2024
AIM: This study aimed to develop highly precise radiomics and deep learning models to accurately detect acute lymphoblastic leukemia (ALL) using a T1WI image.
Development of an immunoinflammatory indicator-related dynamic nomogram based on machine learning for the prediction of intravenous immunoglobulin-resistant Kawasaki disease patients.
International immunopharmacology
May 3, 2024
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
May 3, 2024
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...
Artificial intelligence improves resident detection of pediatric and young adult upper extremity fractures.
Skeletal radiology
May 2, 2024
PURPOSE: We wished to evaluate if an open-source artificial intelligence (AI) algorithm ( https://www.childfx.com ) could improve performance of (1) subspecialized musculoskeletal radiologists, (2) radiology residents, and (3) pediatric residents in ...
Deep Learning Models for Abdominal CT Organ Segmentation in Children: Development and Validation in Internal and Heterogeneous Public Datasets.
AJR. American journal of roentgenology
May 1, 2024
Deep learning abdominal organ segmentation algorithms have shown excellent results in adults; validation in children is sparse. The purpose of this article is to develop and validate deep learning models for liver, spleen, and pancreas segmentation...
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