Large-scale mass spectrometry data combined with demographics analysis rapidly predicts methicillin resistance in Staphylococcus aureus.

Zhuo WangHsin-Yao WangChia-Ru ChungJorng-Tzong HorngJang-Jih LuTzong-Yi Lee

Published in: Briefings in bioinformatics (2021)

Our predictive model facilitates early detection for methicillin resistance of patients with S. aureus infection. The large-scale antibiotic resistance study has unbiasedly highlighted putative candidates that could improve trials of treatment efficiency and inform on prescriptions.

Keyphrases

staphylococcus aureus
mass spectrometry
methicillin resistant staphylococcus aureus
biofilm formation
electronic health record
big data
escherichia coli
machine learning
capillary electrophoresis
gas chromatography
data analysis
pseudomonas aeruginosa
ms ms
artificial intelligence
smoking cessation