Integrating MALDI-TOF Mass Spectrometry with Machine Learning Techniques for Rapid Antimicrobial Resistance Screening of Foodborne Bacterial Pathogens
Author:
Publisher
Springer US
Link
https://link.springer.com/content/pdf/10.1007/978-1-0716-4100-2_6
Reference30 articles.
1. WHO (2020) Antimicrobial resistance. https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance. Accessed 17 Nov 2021
2. O’Neill J (2016) Tackling drug-resistant infections globally: final report and recommendations. Arch Pharm Pract 7:110. https://doi.org/10.4103/2045-080x.186181
3. Murray CJ, Ikuta KS, Sharara F et al (2022) Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet 399:629–655. https://doi.org/10.1016/S0140-6736(21)02724-0
4. Tao Q, Wu Q, Zhang Z et al (2022) Meta-analysis for the global prevalence of foodborne pathogens exhibiting antibiotic resistance and biofilm formation. Front Microbiol 13:906490. https://doi.org/10.3389/fmicb.2022.906490
5. EFSA, ECDC (2022) The European Union one health 2021 zoonoses report. EFSA J 19:e07666. https://doi.org/10.2903/j.efsa.2021.6971
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