BACKGROUND: Machine learning is pivotal for predicting Peripherally Inserted Central Catheter-related venous thrombosis (PICC-RVT) risk, facilitating early diagnosis and proactive treatment. Existing models often assess PICC-RVT risk as static and di...
Advances in neonatal care : official journal of the National Association of Neonatal Nurses
31815770
BACKGROUND: Peripheral intravenous catheters connected to an infusion pump are necessary for the delivery of fluids, nutrition, and medications to hospitalized neonates but are not without complications. These adverse events contribute to hospital-ac...
Computer methods and programs in biomedicine
32738678
BACKGROUND AND OBJECTIVE: Peripherally inserted central catheter (PICC) is a novel drug delivery mode which has been widely used in clinical practice. However, long-term retention and some improper actions of patients may cause some severe complicati...
BACKGROUND: Peripherally inserted central catheters have been extensively applied in clinical practices. However, they are associated with an increased risk of thrombosis. To improve patient care, it is critical to timely identify patients at risk of...
BACKGROUND: Ultrasound guidance increases the success rate of peripheral intravenous catheter placement. However, the longer time required to obtain ultrasound-guided access poses difficulties for ultrasound beginners. Notably, interpretation of ultr...
OBJECTIVE: To establish a prediction model of upper extremity deep vein thrombosis (UEDVT) associated with peripherally inserted central catheter (PICC) based on machine learning (ML), and evaluate the effect.
Journal of the American Heart Association
38761075
BACKGROUND: Patients with chronic limb-threatening ischemia (CLTI) face a high long-term mortality risk. Identifying novel mortality predictors and risk profiles would enable individual health care plan design and improved survival. We aimed to lever...
This study aims to use patient feature and catheterization technology feature variables to train the corresponding machine learning (ML) models to predict peripherally inserted central catheters-deep vein thrombosis (PICCs-DVT) and analyze the import...
Studies in health technology and informatics
39049337
This study presents a deep learning model to predict phlebitis in patients with peripheral intravenous catheter (PIVC) insertions. Leveraging electronic health record data from 27,532 admissions and 70,293 PIVC events at a hospital in Seoul, South Ko...
Techniques in vascular and interventional radiology
39828382
The integration of robotic systems in image-guided trans-arterial interventions has revolutionized the field of Interventional Radiology (IR), offering enhanced precision, safety, and efficiency. These advancements are particularly impactful for acut...