AIMC Topic: Infant, Premature
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Deep learning synthetic angiograms for individuals unable to undergo contrast-guided laser treatment in aggressive retinopathy of prematurity.
Eye (London, England)
Feb 1, 2023
Response to: 'Deep learning synthetic angiograms for individuals unable to undergo contrast-guided laser treatment in aggressive retinopathy of prematurity'.
Eye (London, England)
Jan 21, 2023
A Deep-Learning-Based Collaborative Edge-Cloud Telemedicine System for Retinopathy of Prematurity.
Sensors (Basel, Switzerland)
Dec 27, 2022
Retinopathy of prematurity is an ophthalmic disease with a very high blindness rate. With its increasing incidence year by year, its timely diagnosis and treatment are of great significance. Due to the lack of timely and effective fundus screening fo...
TwinEDA: a sustainable deep-learning approach for limb-position estimation in preterm infants' depth images.
Medical & biological engineering & computing
Nov 28, 2022
Early diagnosis of neurodevelopmental impairments in preterm infants is currently based on the visual analysis of newborns' motion patterns by trained operators. To help automatize this time-consuming and qualitative procedure, we propose a sustainab...
Using machine learning to impact on long-term clinical care: principles, challenges, and practicalities.
Pediatric research
Jul 29, 2022
The rise of machine learning in healthcare has significant implications for paediatrics. Long-term conditions with significant disease heterogeneity comprise large portions of the routine work performed by paediatricians. Improving outcomes through d...
Machine learning methods to predict attrition in a population-based cohort of very preterm infants.
Scientific reports
Jun 22, 2022
The timely identification of cohort participants at higher risk for attrition is important to earlier interventions and efficient use of research resources. Machine learning may have advantages over the conventional approaches to improve discriminati...
Machine learning for understanding and predicting neurodevelopmental outcomes in premature infants: a systematic review.
Pediatric research
May 31, 2022
BACKGROUND: Machine learning has been attracting increasing attention for use in healthcare applications, including neonatal medicine. One application for this tool is in understanding and predicting neurodevelopmental outcomes in preterm infants. In...
Early severity prediction of BPD for premature infants from chest X-ray images using deep learning: A study at the 28th day of oxygen inhalation.
Computer methods and programs in biomedicine
May 10, 2022
BACKGROUND AND OBJECTIVE: Bronchopulmonary dysplasia is a common respiratory disease in premature infants. The severity is diagnosed at the 56th day after birth or discharge by analyzing the clinical indicators, which may cause the delay of the best ...
Camera fusion for real-time temperature monitoring of neonates using deep learning.
Medical & biological engineering & computing
May 3, 2022
The continuous monitoring of vital signs is a crucial aspect of medical care in neonatal intensive care units. Since cable-based sensors pose a potential risk for the immature skin of preterm infants, unobtrusive monitoring techniques using camera sy...
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