AIMC Topic: Infant

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Deep learning of birth-related infant clavicle fractures: a potential virtual consultant for fracture dating.

Pediatric radiology
BACKGROUND: In infant abuse investigations, dating of skeletal injuries from radiographs is desirable to reach a clear timeline of traumatic events. Prior studies have used infant birth-related clavicle fractures as a surrogate to develop a framework...

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
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
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...

Predicting exclusive breastfeeding in maternity wards using machine learning techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Adequate support in maternity wards is decisive for breastfeeding outcomes during the first year of life. Quality improvement interventions require the identification of the factors influencing hospital benchmark indicators....

Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation: Facilitating use of this technology in low resource settings of South Asia and East Africa.

Journal of global health
BACKGROUND: Knowledge of gestational age is critical for guiding preterm neonatal care. In the last decade, metabolic gestational dating approaches emerged in response to a global health need; because in most of the developing world, accurate antenat...

iCatcher: A neural network approach for automated coding of young children's eye movements.

Infancy : the official journal of the International Society on Infant Studies
Infants' looking behaviors are often used for measuring attention, real-time processing, and learning-often using low-resolution videos. Despite the ubiquity of gaze-related methods in developmental science, current analysis techniques usually involv...

Machine learning predicts blood lactate levels in children after cardiac surgery in paediatric ICU.

Cardiology in the young
BACKGROUND: Although serum lactate levels are widely accepted markers of haemodynamic instability, an alternative method to evaluate haemodynamic stability/instability continuously and non-invasively may assist in improving the standard of patient ca...

Ultrasound Lung Image under Artificial Intelligence Algorithm in Diagnosis of Neonatal Respiratory Distress Syndrome.

Computational and mathematical methods in medicine
In order to analyze the application of ultrasonic lung imaging diagnosis model based on artificial intelligence algorithm in neonatal respiratory distress syndrome (NRDS), an ultrasonic lung imaging diagnosis model based on a deep residual network (D...

A Multistage Heterogeneous Stacking Ensemble Model for Augmented Infant Cry Classification.

Frontiers in public health
Understanding the reason for an infant's cry is the most difficult thing for parents. There might be various reasons behind the baby's cry. It may be due to hunger, pain, sleep, or diaper-related problems. The key concept behind identifying the reaso...