Nanomotion technology in combination with machine learning: a new approach for a rapid antibiotic susceptibility test for Mycobacterium tuberculosis-Reference-Cited by-同舟云学术

Nanomotion technology in combination with machine learning: a new approach for a rapid antibiotic susceptibility test for Mycobacterium tuberculosis

Published:2023-09 Issue:7 Volume:25 Page:105151
ISSN:1286-4579
Container-title:Microbes and Infection
language:en
Short-container-title:Microbes and Infection

Author:

Vocat Anthony,Sturm Alexander,Jóźwiak Grzegorz,Cathomen Gino,Świątkowski Michał,Buga Roxana^ORCID,Wielgoszewski Grzegorz^ORCID,Cichocka Danuta^ORCID,Greub Gilbert,Opota Onya^ORCID

Publisher

Elsevier BV

Subject

Infectious Diseases,Immunology,Microbiology

Reference35 articles.

1. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis;Murray;Lancet,2022

2. Updating the approaches to define susceptibility and resistance to anti-tuberculosis agents: implications for diagnosis and treatment;Antimycobacterial Susceptibility Testing;Eur Respir J,2022

3. Combination of fluorescence microscopy and nanomotion detection to characterize bacteria;Aghayee;J Mol Recogn,2013

4. Universal regimens or universal access to drug susceptibility testing for tuberculosis?;Acquah;Lancet Infect Dis,2019

5. Updating the approaches to define susceptibility and resistance to anti-tuberculosis agents: implications for diagnosis and treatment;Antimycobacterial Susceptibility Testing;Eur Respir J,2022

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1. Nanomotion technology for testing azithromycin susceptibility ofSalmonella enterica;2024-09-06

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3. One-day phenotypic drug susceptibility testing forMycobacterium tuberculosisvariantbovisBCG using single-cell imaging and a deep neural network;2024-05-20

4. Yeast Biotechnology 6.0;Fermentation;2024-03-19

5. Accurate and rapid antibiotic susceptibility testing using a machine learning-assisted nanomotion technology platform;Nature Communications;2024-03-18