AIMC Topic: Infant, Newborn

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A Deep-Learning-Based Collaborative Edge-Cloud Telemedicine System for Retinopathy of Prematurity.

Sensors (Basel, Switzerland)
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...

On usage of artificial intelligence for predicting mortality during and post-pregnancy: a systematic review of literature.

BMC medical informatics and decision making
BACKGROUND: Care during pregnancy, childbirth and puerperium are fundamental to avoid pathologies for the mother and her baby. However, health issues can occur during this period, causing misfortunes, such as the death of the fetus or neonate. Predic...

From computer to bedside, involving neonatologists in artificial intelligence models for neonatal medicine.

Pediatric research
In recent years, data have become the main driver of medical innovation. With increased availability and decreased price of storage and computing power, the potential for improvement in care is enormous. Many data-driven explorations have started. Ho...

Artificial Intelligence in Pediatric Nephrology-A Call for Action.

Advances in kidney disease and health
Artificial intelligence is playing an increasingly important role in many fields of clinical care to assist health care providers in patient management. In adult-focused nephrology, artificial intelligence is beginning to be used to improve clinical ...

Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring. Part 2: artificial intelligence.

Pediatric research
BACKGROUND: With the development of Artificial Intelligence (AI) techniques, smart health monitoring, particularly neonatal cardiorespiratory monitoring with wearable devices, is becoming more popular. To this end, it is crucial to investigate the tr...

Multi-layer perceptron classification & quantification of neuronal survival in hypoxic-ischemic brain image slices using a novel gradient direction, grey level co-occurrence matrix image training.

PloS one
Hypoxic ischemic encephalopathy (HIE) is a major global cause of neonatal death and lifelong disability. Large animal translational studies of hypoxic ischemic brain injury, such as those conducted in fetal sheep, have and continue to play a key role...

TwinEDA: a sustainable deep-learning approach for limb-position estimation in preterm infants' depth images.

Medical & biological engineering & computing
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...

Pivotal challenges in artificial intelligence and machine learning applications for neonatal care.

Seminars in fetal & neonatal medicine
Clinical decision support systems (CDSS) that are developed based on artificial intelligence and machine learning (AI/ML) approaches carry transformative potentials in improving the way neonatal care is practiced. From the use of the data available f...

Multilayer dynamic ensemble model for intensive care unit mortality prediction of neonate patients.

Journal of biomedical informatics
Robust and rabid mortality prediction is crucial in intensive care units because it is considered one of the critical steps for treating patients with serious conditions. Combining mortality prediction with the length of stay (LoS) prediction adds an...