Identification of Staphylococcus aureus, Enterococcus faecium, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii from Raman spectra by Artificial Intelligent Raman Detection and Identification System (AIRDIS) with machine learning

Identification of Staphylococcus aureus, Enterococcus faecium, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii from Raman spectra by Artificial Intelligent Raman Detection and Identification System (AIRDIS) with machine learning

Background: Rapid and accurate identification of bacteria is required in order to develop effective treatment strategies. Traditional culture-based methods are time-consuming, while MALDI-TOF MS is expensive. The Raman spectroscopy, due to its relatively cost-effectiveness, offers a promising altern...

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Bibliographic Details
Main Authors: Yu-Tzu Lin, Hsiu-Hsien Lin, Chih-Hao Chen, Kun-Hao Tseng, Pang-Chien Hsu, Ya-Lun Wu, Wei-Cheng Chang, Nai-Shun Liao, Yi-Fan Chou, Chun-Yi Hsu, Yu-Hui Liao, Mao-Wang Ho, Shih-Sheng Chang, Po-Ren Hsueh, Der-Yang Cho
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:Journal of Microbiology, Immunology and Infection
Subjects:
Raman spectroscopy
MALDI-TOF MS
Artificial intelligence
Machine learning
Species identification
Online Access:http://www.sciencedirect.com/science/article/pii/S1684118224002202
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