AIMC Topic: Cross Infection
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Early detection of ICU-acquired infections using high-frequency electronic health record data.
BMC medical informatics and decision making
Jul 21, 2025
BACKGROUND: Nosocomial infections are a major cause of morbidity and mortality in the ICU. Earlier identification of these complications may facilitate better clinical management and improve outcomes. We developed a dynamic prediction model that leve...
The future of healthcare-associated infection surveillance: Automated surveillance and using the potential of artificial intelligence.
Journal of internal medicine
Jun 5, 2025
Healthcare-associated infections (HAIs) are common adverse events, and surveillance is considered a core component of effective HAI reduction programmes. Recently, efforts have focused on automating the traditional manual surveillance process by util...
Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.
Scientific reports
Jun 5, 2025
The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public health problem. This study aims to identify the risk factors of CRPA infection and construct a machine learning model to provide a prediction tool for ...
Predicting infections with multidrug-resistant organisms (MDROs) in neurocritical care patients with hospital-acquired pneumonia (HAP): development of a novel multivariate prediction model.
Microbiology spectrum
May 15, 2025
Hospital-acquired pneumonia (HAP) is prevalent in the neuro-intensive care unit (NICU), significantly increasing susceptibility to infections with multidrug-resistant organisms (MDROs), which result in high mortality rates and substantial healthcare ...
Constructing a screening model to identify patients at high risk of hospital-acquired influenza on admission to hospital.
Frontiers in public health
Apr 16, 2025
OBJECTIVE: To develop a machine learning (ML)-based admission screening model for hospital-acquired (HA) influenza using routinely available data to support early clinical intervention.
Artificial intelligence in hospital infection prevention: an integrative review.
Frontiers in public health
Apr 2, 2025
BACKGROUND: Hospital-acquired infections (HAIs) represent a persistent challenge in healthcare, contributing to substantial morbidity, mortality, and economic burden. Artificial intelligence (AI) offers promising potential for improving HAIs preventi...
Predictive modelling of hospital-acquired infection in acute ischemic stroke using machine learning.
Scientific reports
Dec 28, 2024
Hospital-acquired infections (HAIs) are serious complication for patients with acute ischemic stroke (AIS), often resulting in poor functional outcomes. However, no existing model can specifically predict HAI in AIS patients. Therefore, we employed t...
Promoting hand hygiene in a chemotherapy day center: the role of a robot.
Antimicrobial resistance and infection control
Dec 21, 2024
BACKGROUND: Hand hygiene is a critical component of infection prevention in healthcare settings. Innovative strategies are required to enhance hand hygiene practices among patients and healthcare workers (HCWs).
A machine-learning model for prediction of Acinetobacter baumannii hospital acquired infection.
PloS one
Dec 5, 2024
BACKGROUND: Acinetobacter baumanni infection is a leading cause of morbidity and mortality in the Intensive Care Unit (ICU). Early recognition of patients at risk for infection allows early proper treatment and is associated with improved outcomes. T...
Antimicrobial efficacy of an experimental UV-C robot in controlled conditions and in a real hospital scenario.
The Journal of hospital infection
Nov 19, 2024
BACKGROUND: Among no-touch automated disinfection devices, ultraviolet-C (UV-C) radiation has been proven to be one of the most effective against a broad spectrum of micro-organisms causing healthcare-associated infections.
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