AIMC Topic: Infant
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Assessment of deep learning image reconstruction (DLIR) on image quality in pediatric cardiac CT datasets type of manuscript: Original research.
PloS one
Aug 26, 2024
BAKGROUND: To evaluate the quantitative and qualitative image quality using deep learning image reconstruction (DLIR) of pediatric cardiac computed tomography (CT) compared with conventional image reconstruction methods.
Risk factors for the time to development of retinopathy of prematurity in premature infants in Iran: a machine learning approach.
BMC ophthalmology
Aug 23, 2024
BACKGROUND: Retinopathy of prematurity (ROP), is a preventable leading cause of blindness in infants and is a condition in which the immature retina experiences abnormal blood vessel growth. The development of ROP is multifactorial; nevertheless, the...
Development of an equation to predict delta bilirubin levels using machine learning.
Clinica chimica acta; international journal of clinical chemistry
Aug 22, 2024
OBJECTIVE: Delta bilirubin (albumin-covalently bound bilirubin) may provide important clinical utility in identifying impaired hepatic excretion of conjugated bilirubin, but it cannot be measured in real-time for diagnostic purposes in clinical labor...
Investigation of emergency department abandonment rates using machine learning algorithms in a single centre study.
Scientific reports
Aug 22, 2024
A critical problem that Emergency Departments (EDs) must address is overcrowding, as it causes extended waiting times and increased patient dissatisfaction, both of which are immediately linked to a greater number of patients who leave the ED early, ...
Performance of two different artificial intelligence (AI) methods for assessing carpal bone age compared to the standard Greulich and Pyle method.
La Radiologia medica
Aug 20, 2024
PURPOSE: Evaluate the agreement between bone age assessments conducted by two distinct machine learning system and standard Greulich and Pyle method.
Modeling the relationship between maternal health and infant behavioral characteristics based on machine learning.
PloS one
Aug 20, 2024
This study investigates the impact of maternal health on infant development by developing a mathematical model that delineates the relationship between maternal health indicators and infant behavioral characteristics and sleep quality. The main contr...
Infants' psychophysiological responses to eye contact with a human and with a humanoid robot.
Biological psychology
Aug 17, 2024
Eye contact with a human and with a humanoid robot elicits attention- and affect-related psychophysiological responses. However, these responses have mostly been studied in adults, leaving their developmental origin poorly understood. In this study, ...
Beyond hand-crafted features for pretherapeutic molecular status identification of pediatric low-grade gliomas.
Scientific reports
Aug 17, 2024
The use of targeted agents in the treatment of pediatric low-grade gliomas (pLGGs) relies on the determination of molecular status. It has been shown that genetic alterations in pLGG can be identified non-invasively using MRI-based radiomic features ...
A Machine Learning Predictive Model for Ureteroscopy Lasertripsy Outcomes in a Pediatric Population-Results from a Large Endourology Tertiary Center.
Journal of endourology
Aug 12, 2024
We aimed to develop machine learning (ML) algorithms for the automated prediction of postoperative ureteroscopy outcomes for pediatric kidney stones based on preoperative characteristics. Data from pediatric patients who underwent ureteroscopy for ...
Artificial intelligence reveals the predictions of hematological indexes in children with acute leukemia.
BMC cancer
Aug 12, 2024
Childhood leukemia is a prevalent form of pediatric cancer, with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) being the primary manifestations. Timely treatment has significantly enhanced survival rates for children with acute ...
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