AIMC Topic: Infant, Newborn

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The Essence and Role of Nurses in the Future of Biomedical and Health Informatics.

Studies in health technology and informatics
The whole healthcare system is evolving fast due to environmental pressure related to pandemics, climate change, personnel shortages, and financial limitations, to name but a few. Nurses are central actors in the sustainability of healthcare systems....

Deep learning based non-contact physiological monitoring in Neonatal Intensive Care Unit.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Preterm babies in the Neonatal Intensive Care Unit (NICU) have to undergo continuous monitoring of their cardiac health. Conventional monitoring approaches are contact-based, making the neonates prone to various nosocomial infections. Video-based mon...

Application of Machine Learning Approaches to Predict Postnatal Growth Failure in Very Low Birth Weight Infants.

Yonsei medical journal
PURPOSE: The aims of the study were to develop and evaluate a machine learning model with which to predict postnatal growth failure (PGF) among very low birth weight (VLBW) infants.

The Analysis of Pain Research through the Lens of Artificial Intelligence and Machine Learning.

Pain physician
BACKGROUND: Traditional pain assessment methods have significant limitations due to the high variability in patient reported pain scores and perception of pain by different individuals. There is a need for generalized and automatic pain detection and...

Heart Murmurs in Children: Evaluation and Management.

American family physician
Up to 8.6% of infants and 80% of children have a heart murmur during their early years of life. The presence of a murmur can indicate conditions ranging from no discernable pathology to acquired or congenital heart disease. In infants with a murmur, ...

Machine Learning Used to Compare the Diagnostic Accuracy of Risk Factors, Clinical Signs and Biomarkers and to Develop a New Prediction Model for Neonatal Early-onset Sepsis.

The Pediatric infectious disease journal
BACKGROUND: Current strategies for risk stratification and prediction of neonatal early-onset sepsis (EOS) are inefficient and lack diagnostic performance. The aim of this study was to use machine learning to analyze the diagnostic accuracy of risk f...

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.

EVALUATION OF ARTIFICIAL INTELLIGENCE-BASED QUANTITATIVE ANALYSIS TO IDENTIFY CLINICALLY SIGNIFICANT SEVERE RETINOPATHY OF PREMATURITY.

Retina (Philadelphia, Pa.)
PURPOSE: To evaluate the screening potential of a deep learning algorithm-derived severity score by determining its ability to detect clinically significant severe retinopathy of prematurity (ROP).