AIMC Topic: Intensive Care Units, Neonatal
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Deep learning models for early and accurate diagnosis of ventilator-associated pneumonia in mechanically ventilated neonates.
Computers in biology and medicine
Mar 3, 2025
BACKGROUND: Early and accurate confirmation of critically ill neonates with a suspected diagnosis of ventilator-associated pneumonia (VAP) can optimize the therapeutic strategy and avoid unnecessary use of empirical antibiotics. We aimed to examine w...
Continuous non-contact monitoring of neonatal activity.
BMC pediatrics
Feb 25, 2025
PURPOSE: Neonatal activity is an important physiological parameter in the neonatal intensive care unit (NICU). The degree of neonatal activity is associated with under and over-sedation and may also indicate the onset of disease. Activity may also ca...
Extraction and evaluation of features of preterm patent ductus arteriosus in chest X-ray images using deep learning.
Scientific reports
Nov 26, 2024
Echocardiography is the gold standard of diagnosis and evaluation of patent ductus arteriosus (PDA), a common condition among preterm infants that can cause hemodynamic abnormalities and increased mortality rates, but this technique requires a skille...
Artificial intelligence and informatics in neonatal resuscitation.
Seminars in perinatology
Oct 11, 2024
Neonatal intensive care unit resuscitative care continually evolves and increasingly relies on data. Data driven precision resuscitation care can be enabled by leveraging informatics tools and artificial intelligence. Despite technological advancemen...
From bytes to bedside: a systematic review on the use and readiness of artificial intelligence in the neonatal and pediatric intensive care unit.
Intensive care medicine
Sep 12, 2024
PURPOSE: Despite its promise to enhance patient outcomes and support clinical decision making, clinical use of artificial intelligence (AI) models at the bedside remains limited. Translation of advancements in AI research into tangible clinical benef...
Comparative analysis of artificial intelligence and expert assessments in detecting neonatal procedural pain.
Scientific reports
Sep 2, 2024
Assessing pain in newborns in the NICU is crucial due to their frequent exposure to painful stimuli, yet it's challenging due to the subjective nature of current methods. This study aimed to evaluate the effectiveness of an AI system designed for aut...
Evaluation of Comfort Behavior Levels of Newborn by Artificial Intelligence Techniques.
The Journal of perinatal & neonatal nursing
Jul 29, 2024
BACKGROUND: One of the scales most frequently used in the evaluation of newborn comfort levels is the Neonatal Comfort Behavior Scale (NCBS). It is important therefore that an increased use of the NCBS is encouraged through a more practical method of...
Comparative analysis of machine learning versus traditional method for early detection of parental depression symptoms in the NICU.
Frontiers in public health
May 28, 2024
INTRODUCTION: Neonatal intensive care unit (NICU) admission is a stressful experience for parents. NICU parents are twice at risk of depression symptoms compared to the general birthing population. Parental mental health problems have harmful long-te...
Performance Evaluation of a Supervised Machine Learning Pain Classification Model Developed by Neonatal Nurses.
Advances in neonatal care : official journal of the National Association of Neonatal Nurses
May 15, 2024
BACKGROUND: Early-life pain is associated with adverse neurodevelopmental consequences; and current pain assessment practices are discontinuous, inconsistent, and highly dependent on nurses' availability. Furthermore, facial expressions in commonly u...
Reassessing acquired neonatal intestinal diseases using unsupervised machine learning.
Pediatric research
Feb 27, 2024
BACKGROUND: Acquired neonatal intestinal diseases have an array of overlapping presentations and are often labeled under the dichotomous classification of necrotizing enterocolitis (which is poorly defined) or spontaneous intestinal perforation, hind...
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