A Pragmatic Machine Learning Model To Predict Carbapenem Resistance-Reference-Cited by-同舟云学术

A Pragmatic Machine Learning Model To Predict Carbapenem Resistance

Published:2021-06-17 Issue:7 Volume:65 Page:
ISSN:0066-4804
Container-title:Antimicrobial Agents and Chemotherapy
language:en
Short-container-title:Antimicrob Agents Chemother

Author:

McGuire Ryan J.¹^ORCID,Yu Sean C.²,Payne Philip R. O.²,Lai Albert M.²,Vazquez-Guillamet M. Cristina³⁴,Kollef Marin H.³^ORCID,Michelson Andrew P.²³

Affiliation:

1. Department of Internal Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA

2. Institute for Informatics, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA

3. Division of Pulmonary and Critical Care Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA

4. Division of Infectious Disease, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA

Abstract

Infection caused by carbapenem-resistant (CR) organisms is a rising problem in the United States. While the risk factors for antibiotic resistance are well known, there remains a large need for the early identification of antibiotic-resistant infections.

Publisher

American Society for Microbiology

Subject

Infectious Diseases,Pharmacology (medical),Pharmacology

Link

https://journals.asm.org/doi/pdf/10.1128/AAC.00063-21

Reference41 articles.

1. Antibiotic resistance threats in the United States, 2019

2. The incremental cost of infections associated with multidrug-resistant organisms in the inpatient hospital setting-A national estimate

3. Understanding the mechanisms and drivers of antimicrobial resistance

4. Predicting Antimicrobial Resistance Prevalence and Incidence from Indicators of Antimicrobial Use: What Is the Most Accurate Indicator for Surveillance in Intensive Care Units?

5. Risk Factors for Development of Carbapenem Resistance Among Gram-Negative Rods

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial intelligence and prescription of antibiotic therapy: present and future;Expert Review of Anti-infective Therapy;2024-08-18

2. From Data to Decisions: Leveraging Artificial Intelligence and Machine Learning in Combating Antimicrobial Resistance – a Comprehensive Review;Journal of Medical Systems;2024-08-01

3. Applications of Machine Learning on Electronic Health Record Data to Combat Antibiotic Resistance;The Journal of Infectious Diseases;2024-07-12

4. Prediction models for diagnosis and prognosis of the colonization or infection of multidrug-resistant organisms in adults: a systematic review, critical appraisal, and meta-analysis;Clinical Microbiology and Infection;2024-07

5. Machine learning to predict antimicrobial resistance: future applications in clinical practice?;Infectious Diseases Now;2024-04