Antimicrobial resistance and infection control
Jul 6, 2024
BACKGROUND: Multidrug-resistant organisms (MDRO) pose a significant threat to public health. Intensive Care Units (ICU), characterized by the extensive use of antimicrobial agents and a high prevalence of bacterial resistance, are hotspots for MDRO p...
BACKGROUND: Nosocomial infections with heavy disease burden are becoming a major threat to the health care system around the world. Through long-term, systematic, continuous data collection and analysis, Nosocomial infection surveillance (NIS) system...
Journal of clinical monitoring and computing
Jun 19, 2024
Hand hygiene among anesthesia personnel is important to prevent hospital-acquired infections in operating rooms; however, an efficient monitoring system remains elusive. In this study, we leverage a deep learning approach based on operating room vide...
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
May 21, 2024
PURPOSE: To use machine learning to examine health equity and clinical outcomes in patients who experienced a nurse sensitive indicator (NSI) event, defined as a fall, a hospital-acquired pressure injury (HAPI) or a hospital-acquired infection (HAI).
BACKGROUND: Hospital-acquired influenza (HAI) is under-recognized despite its high morbidity and poor health outcomes. The early detection of HAI is crucial for curbing its transmission in hospital settings.
We present a novel methodology for integrating high resolution longitudinal data with the dynamic prediction capabilities of survival models. The aim is two-fold: to improve the predictive power while maintaining the interpretability of the models. T...
American journal of infection control
Mar 14, 2024
BACKGROUND: Health care-associated infection (HAI) surveillance is vital for safety in health care settings. It helps identify infection risk factors, enhancing patient safety and quality improvement. However, HAI surveillance is complex, demanding s...
This work describes a novel artificial intelligence-based training and monitoring system (AITMS) that was used to control and prevent nosocomial infections (NIs) by improving the skills of donning/removing personal protective equipment (PPE). The AIT...
The goal of this study was to evaluate matrix-assisted laser desorption ionization-iime of flight mass spectrometry (MALDI-TOF MS) and Fourier-transform infrared spectroscopy (FTIR-S) as diagnostic alternatives to DNA-based methods for the detection ...
BACKGROUND: Machine learning (ML) models for early identification of patients at risk of hospital-acquired urinary tract infection (HA-UTI) may enable timely and targeted preventive and therapeutic strategies. However, clinicians are often challenged...
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