AIMC Topic: Central Venous Catheters

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Predicting central line-associated bloodstream infections and mortality using supervised machine learning.

Journal of critical care Feb 21, 2018
PURPOSE: The purpose of this study was to compare machine learning techniques for predicting central line-associated bloodstream infection (CLABSI).
Humans Databases, Factual Intensive Care Units Female Male Middle Aged Risk Assessment Hospital Mortality Bacteremia Logistic Models Predictive Value of Tests Central Venous Catheters Catheter-Related Infections Supervised Machine Learning Florida Simplified Acute Physiology Score
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Predicting outcomes in central venous catheter salvage in pediatric central line-associated bloodstream infection.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
OBJECTIVE: Central line-associated bloodstream infections (CLABSIs) are a common, costly, and hazardous healthcare-associated infection in children. In children in whom continued access is critical, salvage of infected central venous catheters (CVCs)...
Humans Machine Learning Anti-Infective Agents Prognosis Female Male Infant Sepsis Adolescent Child, Preschool Child ROC Curve Treatment Outcome Area Under Curve Central Venous Catheters Cross Infection Recurrence
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A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection.

Journal of digital imaging Aug 1, 2018
A peripherally inserted central catheter (PICC) is a thin catheter that is inserted via arm veins and threaded near the heart, providing intravenous access. The final catheter tip position is always confirmed on a chest radiograph (CXR) immediately a...
Humans Neural Networks, Computer Patient Safety Databases, Factual Retrospective Studies Female Male Deep Learning Electrocardiography Catheterization, Peripheral Catheterization, Central Venous Central Venous Catheters Pattern Recognition, Automated Radiography, Thoracic
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