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...
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).
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...
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.
Anaesthesia, critical care & pain medicine
Oct 2, 2024
BACKGROUND: Sepsis is a threat to global health, and domestically is the major cause of in-hospital mortality. Due to increases in inpatient morbidity and mortality resulting from sepsis, healthcare providers (HCPs) would accrue significant benefits ...
American journal of infection control
Sep 21, 2024
BACKGROUND: Hospital-acquired infections (HAIs) increase morbidity, mortality, and health care costs. Effective hand hygiene (HH) is crucial for prevention, but achieving high compliance remains challenge. This study explores using machine learning t...
This retrospective study used 10 machine learning algorithms to predict the risk of healthcare-associated infections (HAIs) in patients admitted to intensive care units (ICUs). A total of 2,517 patients treated in the ICU of a tertiary hospital in Ch...
Antimicrobial resistance and infection control
Aug 7, 2024
BACKGROUND: Nosocomial infections (NIs) frequently occur and adversely impact prognosis for hospitalized patients with cirrhosis. This study aims to develop and validate two machine learning models for NIs and in-hospital mortality risk prediction.
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