AIMC Topic: Infant, Premature
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Listening deeper: neural networks unravel acoustic features in preterm infant crying.
Scientific reports
Jul 2, 2025
Early infant crying provides critical insights into neurodevelopment, with atypical acoustic features linked to conditions such as preterm birth. However, previous studies have focused on limited and specific acoustic features, hindering a more compr...
Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection.
Scientific reports
Jul 2, 2025
In general, deficient birth weight neonates suffer from hypoglycemia, and this can be quite disadvantageous. Like oxygen, glucose is a building block of life and constitutes the significant share of energy produced by the fetus and the neonate during...
Development and external validation of a machine learning model to predict bronchopulmonary dysplasia using dynamic factors.
Scientific reports
Apr 19, 2025
We hypothesized that incorporating postnatal dynamic factors would enhance the prediction accuracy of bronchopulmonary dysplasia in preterm infants. This retrospective cohort study included neonates born before 32 weeks of gestation at Seoul National...
Prediction of retinopathy of prematurity development and treatment need with machine learning models.
BMC ophthalmology
Apr 10, 2025
BACKGROUND: To evaluate the effectiveness of machine learning (ML) models in predicting the occurrence of retinopathy of prematurity (ROP) and treatment need.
AI-Enabled Screening for Retinopathy of Prematurity in Low-Resource Settings.
JAMA network open
Apr 1, 2025
IMPORTANCE: Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness worldwide. If detected and treated early, ROP-associated blindness is preventable; however, identifying patients who might respond to treatment requi...
Do Treatment Choices by Artificial Intelligence Correspond to Reality? Retrospective Comparative Research with Necrotizing Enterocolitis as a Use Case.
Medical decision making : an international journal of the Society for Medical Decision Making
Mar 12, 2025
BackgroundIn cases of surgical necrotizing enterocolitis (NEC), the choice between laparotomy (LAP) or comfort care (CC) presents a complex, ethical dilemma. A behavioral artificial intelligence technology (BAIT) decision aid was trained on expert kn...
Retinal Vascularization Rate Predicts Retinopathy of Prematurity and Remains Unaffected by Low-Dose Bevacizumab Treatment.
American journal of ophthalmology
Mar 5, 2025
PURPOSE: To assess the rate of retinal vascularization derived from ultra-widefield (UWF) imaging-based retinopathy of prematurity (ROP) screening as predictor of type 1 ROP and characterize the effect of anti-vascular endothelial growth factor (anti...
Development of a machine learning model for prediction of intraventricular hemorrhage in premature neonates.
Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
Dec 16, 2024
PURPOSE: Intraventricular hemorrhage (IVH) is a common and severe complication in premature neonates, leading to long-term neurological impairments. Early prediction and identification of risk factors for IVH in premature neonates are crucial for imp...
Automatic Segmentation of Sylvian Fissure in Brain Ultrasound Images of Pre-Term Infants Using Deep Learning Models.
Ultrasound in medicine & biology
Dec 15, 2024
OBJECTIVE: Segmentation of brain sulci in pre-term infants is crucial for monitoring their development. While magnetic resonance imaging has been used for this purpose, cranial ultrasound (cUS) is the primary imaging technique used in clinical practi...
Extraction and evaluation of features of preterm patent ductus arteriosus in chest X-ray images using deep learning.
Scientific reports
Nov 26, 2024
Echocardiography is the gold standard of diagnosis and evaluation of patent ductus arteriosus (PDA), a common condition among preterm infants that can cause hemodynamic abnormalities and increased mortality rates, but this technique requires a skille...
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