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Intensive Care Units, Neonatal

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Automatic and Continuous Discomfort Detection for Premature Infants in a NICU Using Video-Based Motion Analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Frequent pain and discomfort in premature infants can lead to long-term adverse neurodevelopmental outcomes. Video-based monitoring is considered to be a promising contactless method for identification of discomfort moments. In this study, we propose...

Predicting the serum digoxin concentrations of infants in the neonatal intensive care unit through an artificial neural network.

BMC pediatrics
BACKGROUND: Given its narrow therapeutic range, digoxin's pharmacokinetic parameters in infants are difficult to predict due to variation in birth weight and gestational age, especially for critically ill newborns. There is limited evidence to suppor...

Reducing False Alarm Rates in Neonatal Intensive Care: A New Machine Learning Approach.

Advances in experimental medicine and biology
UNLABELLED: In neonatal intensive care units (NICUs), 87.5% of alarms by the monitoring system are false alarms, often caused by the movements of the neonates. Such false alarms are not only stressful for the neonates as well as for their parents and...

Machine Learning to Support Hemodynamic Intervention in the Neonatal Intensive Care Unit.

Clinics in perinatology
Hemodynamic support in neonatal intensive care is directed at maintaining cardiovascular wellbeing. At present, monitoring of vital signs plays an essential role in augmenting care in a reactive manner. By applying machine learning techniques, a mode...

Workforce Shortage for Retinopathy of Prematurity Care and Emerging Role of Telehealth and Artificial Intelligence.

Pediatric clinics of North America
Retinopathy of prematurity (ROP) is the leading cause of childhood blindness in very-low-birthweight and very preterm infants in the United States. With improved survival of smaller babies, more infants are at risk for ROP, yet there is an increasing...

[Application of the artificial intelligence-rapid whole-genome sequencing diagnostic system in the neonatal/pediatric intensive care unit].

Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics
Pediatric patients in the neonatal intensive care unit (NICU) and the pediatric intensive care unit (PICU) have a high incidence rate of genetic diseases, and early rapid etiological diagnosis and targeted interventions can help to reduce mortality o...

Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates.

Computers in biology and medicine
Premature birth is the primary risk factor in neonatal deaths, with the majority of extremely premature babies cared for in neonatal intensive care units (NICUs). Mortality risk prediction in this setting can greatly improve patient outcomes and reso...

Mining tasks and task characteristics from electronic health record audit logs with unsupervised machine learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The characteristics of clinician activities while interacting with electronic health record (EHR) systems can influence the time spent in EHRs and workload. This study aims to characterize EHR activities as tasks and define novel, data-dri...

RGB-D scene analysis in the NICU.

Computers in biology and medicine
Continuity of care is achieved in the neonatal intensive care unit (NICU) through careful documentation of all events of clinical significance, including clinical interventions and routine care events (e.g., feeding, diaper change, weighing, etc.). A...

Artificial Intelligence to Improve Health Outcomes in the NICU and PICU: A Systematic Review.

Hospital pediatrics
CONTEXT: Artificial intelligence (AI) technologies are increasingly used in pediatrics and have the potential to help inpatient physicians provide high-quality care for critically ill children.