Raman spectrum combined with deep learning for precise recognition of Carbapenem-resistant Enterobacteriaceae-Reference-Cited by-同舟云学术

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Raman spectrum combined with deep learning for precise recognition of Carbapenem-resistant Enterobacteriaceae

Published:2024-02-21 Issue:10 Volume:416 Page:2465-2478
ISSN:1618-2642
Container-title:Analytical and Bioanalytical Chemistry
language:en
Short-container-title:Anal Bioanal Chem

Author:

Wang Wen,Wang Xin,Huang Ya,Zhao Yi,Fang Xianglin,Cong Yanguang,Tang Zhi,Chen Luzhu,Zhong Jingyi,Li Ruoyi,Guo Zhusheng,Zhang Yanjiao,Li Shaoxin

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00216-024-05209-9.pdf

Reference40 articles.

1. Potter RF, D’Souza AW, Dantas G. The rapid spread of carbapenem-resistant Enterobacteriaceae. Drug Resist Updat. 2016;29:30–46. https://doi.org/10.1016/j.drup.2016.09.002.

2. Armstrong T, Fenn SJ, Hardie KR. JMM Profile: Carbapenems: a broad-spectrum antibiotic. J Med Microbiol. 2021;70: 001462. https://doi.org/10.1099/jmm.0.001462.

3. Willyard C. The drug-resistant bacteria that pose the greatest health threats. Nature. 2017;543:15. https://doi.org/10.1038/nature.2017.21550.

4. Pokharel K, Dawadi BR, Bhatt CP, Gupte S, Jha B. Resistance pattern of carbapenem on Enterobacteriaceae. JNMA J Nepal Med Assoc. 2018;56:931–5. https://doi.org/10.31729/jnma.4006.

5. Morrill HJ, Pogue JM, Kaye KS, LaPlante KL. Treatment options for carbapenem-resistant Enterobacteriaceae infections. Open Forum Infect Dis. 2015;2:ofv050. https://doi.org/10.1093/ofid/ofv050.

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1. Machine Learning-Assisted Raman Spectroscopy and SERS for Bacterial Pathogen Detection: Clinical, Food Safety, and Environmental Applications;Chemosensors;2024-07-15

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