AI Medical Compendium Topic

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Rapid Discrimination of ST175 Isolates Involved in a Nosocomial Outbreak Using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy Coupled with Machine Learning.

Transboundary and emerging diseases
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 ...

A machine-learning model for prediction of Acinetobacter baumannii hospital acquired infection.

PloS one
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
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.

Predictive modelling of hospital-acquired infection in acute ischemic stroke using machine learning.

Scientific reports
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
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).

Constructing a screening model to identify patients at high risk of hospital-acquired influenza on admission to hospital.

Frontiers in public health
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
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...

Are AI-based surveillance systems for healthcare-associated infections ready for clinical practice? A systematic review and meta-analysis.

Artificial intelligence in medicine
Healthcare-associated infections (HAIs) are a global public health concern, imposing significant clinical and financial burdens. Despite advancements, surveillance methods remain largely manual and resource-intensive, often leading to underreporting....

Harnessing artificial intelligence for infection control and prevention in hospitals: A comprehensive review of current applications, challenges, and future directions.

Saudi medical journal
Hospital-acquired infections (HAIs) significantly burden global healthcare systems, exacerbated by antibiotic-resistant bacteria. Traditional infection control measures often lack consistency due to variable human compliance. This comprehensive revie...