AIMC Topic: Antimicrobial Stewardship

Clear Filters Showing 11 to 20 of 24 articles

Explainable and Interpretable Machine Learning for Antimicrobial Stewardship: Opportunities and Challenges.

Clinical therapeutics
There is growing interest in exploiting the advances in artificial intelligence and machine learning (ML) for improving and monitoring antimicrobial prescriptions in line with antimicrobial stewardship principles. Against this background, the concept...

Development of a Machine Learning Model Using Electronic Health Record Data to Identify Antibiotic Use Among Hospitalized Patients.

JAMA network open
IMPORTANCE: Comparisons of antimicrobial use among hospitals are difficult to interpret owing to variations in patient case mix. Risk-adjustment strategies incorporating larger numbers of variables haves been proposed as a method to improve compariso...

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...

Identifying predictors of antimicrobial exposure in hospitalized patients using a machine learning approach.

Journal of applied microbiology
AIMS: Analysis and tracking of antimicrobial utilization (AU) are crucial in antimicrobial stewardship efforts which are used to find effective interventions for controlling antimicrobial resistance. In antimicrobial stewardship, standard risk adjust...

Using natural language processing and VetCompass to understand antimicrobial usage patterns in Australia.

Australian veterinary journal
BACKGROUND: Currently there is an incomplete understanding of antimicrobial usage patterns in veterinary clinics in Australia, but such knowledge is critical for the successful implementation and monitoring of antimicrobial stewardship programs.

Rapid Rule Out of Culture-Negative Bloodstream Infections by Use of a Novel Approach to Universal Detection of Bacteria and Fungi.

The journal of applied laboratory medicine
BACKGROUND: Currently it can take up to 5 days to rule out bloodstream infection. With the low yield of blood cultures (approximately 10%), a significant number of patients are potentially exposed to inappropriate therapy that can lead to adverse eve...

Comparison of the Abbott Architect BRAHMS and the Biomérieux Vidas BRAHMS Procalcitonin Assays.

The journal of applied laboratory medicine
BACKGROUND: Procalcitonin (PCT) is a well-established marker for bacterial infection. Recently the US Food and Drug Administration approved the expanded use of this biomarker to guide clinical decisions for antibiotic treatment in patients with lower...

Practical considerations for implementation of syndromic panel and diagnostic stewardship in the era of syndromic panel testing.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
BACKGROUND: The significant advancements in the development of syndromic panel testing for infectious diseases have brought about a paradigm shift in the clinical microbiology laboratory and the practices of Infectious Diseases Physicians. Due to the...

Evaluating the impact of artificial intelligence in antimicrobial stewardship: a comparative meta-analysis with traditional risk scoring systems.

Infectious diseases now
OBJECTIVES: The growing challenge of antimicrobial resistance (AMR) has underscored the urgent need for robust antimicrobial stewardship programs (AMS). Artificial intelligence (AI) and machine learning (ML) have emerged as promising tools to support...

Patient prioritization for pharmaceutical intervention in the hospital setting: a retrospective cross-sectional study.

The International journal of pharmacy practice
OBJECTIVES: Prioritization of patients requiring pharmaceutical intervention is critical given limited resources. Data from pharmacy software could be used to target patients. This retrospective cross-sectional study aimed to describe the method impl...