Employing Machine Learning for the Prediction of Antimicrobial Resistance (AMR) Phenotypes-Reference-Cited by-同舟云学术

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Employing Machine Learning for the Prediction of Antimicrobial Resistance (AMR) Phenotypes

Published:2024-03-15 Issue: Volume: Page:1519-1524
ISSN:
Container-title:SoutheastCon 2024
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Author:

Kim Donghoon¹,Jun Se-ran²,Hwang Doosung³

Affiliation:

1. Arkansas State University,Department of Computer Science,Jonesboro,AR,USA

2. University of Arkansas for Medical Sciences,Department of Biomedical Informatics,Little Rock,AR,USA

3. Dankook University,Department of Software Science,Yongin,South Korea

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10500015/10500024/10500051.pdf?arnumber=10500051

Reference32 articles.

1. Antibiotic resistance: a geopolitical issue

2. Book review: Tackling drug-resistant infections globally

3. Utilizing Paper‐Based Devices for Antimicrobial‐Resistant Bacteria Detection

4. A systematic review on antibiotics misuse in livestock and aquaculture and regulation implications in China

5. Author Correction: Antibiotic drug-resistance as a complex system driven by socio-economic growth and antibiotic misuse

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