Evaluation of Machine Learning Models for Predicting Antimicrobial Resistance of Actinobacillus pleuropneumoniae From Whole Genome Sequences

Antimicrobial resistance (AMR) is becoming a huge problem in countries all over the world, and new approaches to identifying strains resistant or susceptible to certain antibiotics are essential in fighting against antibiotic-resistant pathogens. Genotype-based machine learning methods showed great...

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Detalles Bibliográficos
Autores principales: Liu, Zhichang, Deng, Dun, Lu, Huijie, Sun, Jian, Lv, Luchao, Li, Shuhong, Peng, Guanghui, Ma, Xianyong, Li, Jiazhou, Li, Zhenming, Rong, Ting, Wang, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Microbiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7016212/
https://www.ncbi.nlm.nih.gov/pubmed/32117101
http://dx.doi.org/10.3389/fmicb.2020.00048

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7016212/
https://www.ncbi.nlm.nih.gov/pubmed/32117101
http://dx.doi.org/10.3389/fmicb.2020.00048

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