Rapid Identification of Methicillin-Resistant Staphylococcus aureus Using MALDI-TOF MS and Machine Learning from over 20,000 Clinical Isolates-Reference-Cited by-同舟云学术

Rapid Identification of Methicillin-Resistant Staphylococcus aureus Using MALDI-TOF MS and Machine Learning from over 20,000 Clinical Isolates

Published:2022-04-27 Issue:2 Volume:10 Page:
ISSN:2165-0497
Container-title:Microbiology Spectrum
language:en
Short-container-title:Microbiol Spectr

Author:

Yu Jiaxin¹,Tien Ni²³,Liu Yu-Ching⁴⁵,Cho Der-Yang⁶,Chen Jia-Wen⁷,Tsai Yin-Tai⁸,Huang Yu-Chen⁹,Chao Huei-Jen¹⁰,Chen Chao-Jung⁴⁵^ORCID

Affiliation:

1. AI Innovation Center, China Medical University Hospital, Taichung City, Taiwan

2. Department of Laboratory Medicine, China Medical University Hospital, Taichung City, Taiwan

3. Department of Medical Laboratory Science and Biotechnology, China Medical University, Taichung City, Taiwan

4. Graduate Institute of Integrated Medicine, China Medical University, Taichung City, Taiwan

5. Proteomics Core Laboratory, Department of Medical Research, China Medical University Hospital, Taichung City, Taiwan

6. Department of Neurosurgery, China Medical University Hospital, Taichung City, Taiwan

7. Laboratory Medicine, Feng Yuan Hospital, Ministry of Health and Welfare, Taichung City, Taiwan

8. Department of Laboratory Medicine, Taipei Medical University-Shuang Ho Hospital, Ministry of Health and Welfare, New Taipei City, Taiwan

9. Department of Laboratory Medicine, National Taiwan University Hospital Yunlin Branch, Yunlin County, Taiwan

10. Department of Laboratory Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien County, Taiwan

Abstract

Over 20,000 clinical MSSA and MRSA isolates were collected to build a machine learning (ML) model to identify MSSA/MRSA and their markers. This model was tested across four external clinical sites to ensure the model’s usability.

Funder

China Medical University Hospital

China Medical University, Taiwan

Ministry of Science and Technology, Taiwan

Publisher

American Society for Microbiology

Subject

Infectious Diseases,Cell Biology,Microbiology (medical),Genetics,General Immunology and Microbiology,Ecology,Physiology

Link

https://journals.asm.org/doi/pdf/10.1128/spectrum.00483-22

Reference22 articles.

1. Innovative and rapid antimicrobial susceptibility testing systems

2. Detection ofmecA, femA, andfemBgenes in clinical strains of staphylococci using polymerase chain reaction

3. Current status of MALDI-TOF mass spectrometry in clinical microbiology

4. Current and Emerging Methods of Antibiotic Susceptibility Testing

5. Peptide Biomarker Discovery for Identification of Methicillin-Resistant and Vancomycin-Intermediate Staphylococcus aureus Strains by MALDI-TOF

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning and matrix-assisted laser desorption/ionization time-of-flight mass spectra for antimicrobial resistance prediction: A systematic review of recent advancements and future development;Journal of Chromatography A;2024-10

2. An antimicrobial drug recommender system using MALDI-TOF MS and dual-branch neural networks;2024-09-03

3. An antimicrobial drug recommender system using MALDI-TOF MS and dual-branch neural networks;2024-09-03

4. Predicting Pseudomonas aeruginosa drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra;mSystems;2024-08-16

5. Proteomic assay for rapid characterisation of Staphylococcus aureus antimicrobial resistance mechanisms directly from blood cultures;European Journal of Clinical Microbiology & Infectious Diseases;2024-05-16