AIMC Topic: Adolescent

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Untrained Network for Super-resolution for Non-contrast-enhanced Wholeheart MRI Acquired using Cardiac-triggered REACT (SRNN-REACT).

Current medical imaging Jan 1, 2024
BACKGROUND: Three-dimensional (3D) whole-heart magnetic resonance imaging (MRI) is an excellent tool to check the heart anatomy of patients with congenital and acquired heart disease. However, most 3D whole-heart MRI acquisitions take a long time to ...
Magnetic Resonance Imaging Heart Heart Diseases Signal-To-Noise Ratio Humans Neural Networks, Computer Adolescent Female Child, Preschool Male Child Infant Imaging, Three-Dimensional
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Data-driven Machine Learning Models for Risk Stratification and Prediction of Emergence Delirium in Pediatric Patients Underwent Tonsillectomy/Adenotonsillectomy.

Annali italiani di chirurgia Jan 1, 2024
AIM: In the pediatric surgical population, Emergence Delirium (ED) poses a significant challenge. This study aims to develop and validate machine learning (ML) models to identify key features associated with ED and predict its occurrence in children ...
Emergence Delirium Adenoidectomy Risk Assessment ROC Curve Adolescent Logistic Models Child, Preschool Humans Support Vector Machine Child Tonsillectomy Machine Learning Female Male
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Predicting Bone Marrow Metastasis in Neuroblastoma: An Explainable Machine Learning Approach Using Contrast-Enhanced Computed Tomography Radiomics Features.

Technology in cancer research & treatment Jan 1, 2024
PURPOSE: To predict bone marrow metastasis in neuroblastoma using contrast-enhanced computed tomography (CECT) radiomics features and explainable machine learning.
Algorithms Contrast Media Retrospective Studies Radiomics Humans Bone Marrow Male Child, Preschool Machine Learning Tomography, X-Ray Computed Bone Marrow Neoplasms Infant Child Female Neuroblastoma Adolescent ROC Curve Support Vector Machine
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Can AI generate diagnostic reports for radiologist approval on CXR images? A multi-reader and multi-case observer performance study.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: Accurately detecting a variety of lung abnormalities from heterogenous chest X-ray (CXR) images and writing radiology reports is often difficult and time-consuming.
Radiography, Thoracic Radiologists Radiographic Image Interpretation, Computer-Assisted Lung Diseases Observer Variation Male Middle Aged Lung Adolescent Humans Artificial Intelligence Retrospective Studies Female Aged Young Adult Adult Sensitivity and Specificity
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Effect of robotic-assisted gait training program on spatiotemporal gait parameters for ambulatory children with cerebral palsy: A randomized control trial.

NeuroRehabilitation Jan 1, 2024
BACKGROUND: Gait training programs are commonly used to improve gait in children with cerebral palsy (CP).
Gait Disorders, Neurologic Robotics Gait Exercise Therapy Cerebral Palsy Humans Female Male Adolescent Child, Preschool Child Treatment Outcome
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Patients' perspectives on the use of artificial intelligence and robots in healthcare.

Bratislavske lekarske listy Jan 1, 2024
OBJECTIVE: We aimed to evaluate the opinions of individuals aged 18 and above in our country regarding the use of artificial intelligence (AI) and robots in the field of healthcare.
Humans Artificial Intelligence Delivery of Health Care Male Trust Middle Aged Surveys and Questionnaires Female Aged Young Adult Adult Adolescent Robotics Bulgaria
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Clinical Application of Automatic Assessment of Scoliosis Cobb Angle Based on Deep Learning.

Current medical imaging Jan 1, 2024
INTRODUCTION: A recently developed deep-learning-based automatic evaluation model provides reliable and efficient Cobb angle measurements for scoliosis diagnosis. However, few studies have explored its clinical application, and external validation is...
Adolescent Female Child Scoliosis Radiography Reproducibility of Results Humans Spine Male Deep Learning
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Deep learning-based differentiation of peripheral high-flow and low-flow vascular malformations in T2-weighted short tau inversion recovery MRI.

Clinical hemorheology and microcirculation Jan 1, 2024
BACKGROUND: Differentiation of high-flow from low-flow vascular malformations (VMs) is crucial for therapeutic management of this orphan disease.
Adolescent Child, Preschool Child Magnetic Resonance Imaging Adult Male Middle Aged Deep Learning Humans Vascular Malformations Female Aged
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A Humane Social Learning-Informed Metaverse: Cultivating Positive Technology Experiences in Digital Learning Environments.

Cyberpsychology, behavior and social networking Jan 1, 2024
Online environments, such as metaverses, provide distinct social environments for people to engage in complex, cognitive, and multidirectional learning and meaning-making experiences. These engaging and influential environments highlight important fa...
Technology Adolescent Cues Humans Social Learning Artificial Intelligence Algorithms
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[Automated cephalometric landmark identification and location based on convolutional neural network].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology Dec 9, 2023
To develop an automated landmark location system applicable to the case of landmark missing. Four and eighty-one lateral cephalograms, which contained 240 males and 241 females, with an average age of (24.5±5.6) years, taken from January 2015 to Ja...
Radiography Cephalometry Orthodontics Young Adult Humans Adult Neural Networks, Computer Male Female Adolescent Reproducibility of Results
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