AIMC Topic: Cross Infection

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Artificial intelligence-based tools to control healthcare associated infections: A systematic review of the literature.

Journal of infection and public health
BACKGROUND: Healthcare-associated infections (HAIs) are the most frequent adverse events in healthcare and a global public health concern. Surveillance is the foundation for effective HAIs prevention and control. Manual surveillance is labor intensiv...

Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
BACKGROUND: Machine learning (ML) is increasingly being used in many areas of health care. Its use in infection management is catching up as identified in a recent review in this journal. We present here a complementary review to this work.

Comprehensive analysis of rule formalisms to represent clinical guidelines: Selection criteria and case study on antibiotic clinical guidelines.

Artificial intelligence in medicine
BACKGROUND: The over-use of antibiotics in clinical domains is causing an alarming increase in bacterial resistance, thus endangering their effectiveness as regards the treatment of highly recurring severe infectious diseases. Whilst Clinical Guideli...

The damage response framework and infection prevention: From concept to bedside.

Infection control and hospital epidemiology
Hospital-acquired infections remain a common cause of morbidity and mortality despite advances in infection prevention through use of bundles, environmental cleaning, antimicrobial stewardship, and other best practices. Current prevention strategies ...

An interpretation algorithm for molecular diagnosis of bacterial vaginosis in a maternity hospital using machine learning: proof-of-concept study.

Diagnostic microbiology and infectious disease
Allplex Bacterial vaginosis assay (Seegene, South Korea) is a molecular test for bacterial vaginosis (BV). A machine learning algorithm was devised on 200 samples (BV = 23, non-BV = 177) converting 7 identified bacterial strains polymerase chain reac...

Biocide susceptibilities and biofilm-forming capacities of Acinetobacter baumannii clinical isolates from Malaysia.

Journal of infection in developing countries
INTRODUCTION: Acinetobacter baumannii is a Gram-negative nosocomial pathogen that has the capacity to develop resistance to all classes of antimicrobial compounds. However, very little is known regarding its susceptibility to biocides (antiseptics an...

Deep Learning versus Conventional Machine Learning for Detection of Healthcare-Associated Infections in French Clinical Narratives.

Methods of information in medicine
OBJECTIVE: The objective of this article was to compare the performances of health care-associated infection (HAI) detection between deep learning and conventional machine learning (ML) methods in French medical reports.

Statistical outbreak detection by joining medical records and pathogen similarity.

Journal of biomedical informatics
We present a statistical inference model for the detection and characterization of outbreaks of hospital associated infection. The approach combines patient exposures, determined from electronic medical records, and pathogen similarity, determined by...