High-Speed Diagnosis of Bacterial Pathogens at the Single Cell Level by Raman Microspectroscopy with Machine Learning Filters and Denoising Autoencoders-Reference-Cited by-同舟云学术

High-Speed Diagnosis of Bacterial Pathogens at the Single Cell Level by Raman Microspectroscopy with Machine Learning Filters and Denoising Autoencoders

Published:2022-01-13 Issue:2 Volume:17 Page:376-385
ISSN:1554-8929
Container-title:ACS Chemical Biology
language:en
Short-container-title:ACS Chem. Biol.

Author:

Xu Jiabao¹^ORCID,Yi Xiaofei²³,Jin Guilan²³,Peng Di²³,Fan Gaoya²³,Xu Xiaogang⁴⁵,Chen Xin⁴⁵,Yin Huabing⁶^ORCID,Cooper Jonathan M.⁶,Huang Wei E.¹^ORCID

Affiliation:

1. Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, U.K.

2. Shanghai Hesen Biotechnology Co., Ltd, Shanghai 201802, China

3. Shanghai D-band Medical Instrument Co., Ltd, Shanghai 201802, China

4. Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai 200040, China

5. National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China

6. James Watt School of Engineering, University of Glasgow, Glasgow G12 8LT, U.K.

Funder

Ministry of Science and Technology of the People's Republic of China

Innovate UK

Science and Technology Commission of Shanghai Municipality

Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences

Publisher

American Chemical Society (ACS)

Subject

Molecular Medicine,General Medicine,Biochemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acschembio.1c00834

Reference37 articles.

1. Prevalence of Inappropriate Antibiotic Prescriptions Among US Ambulatory Care Visits, 2010-2011

2. Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning

3. Direct analysis of clinical relevant single bacterial cells from cerebrospinal fluid during bacterial meningitis by means of micro-Raman spectroscopy

4. Vibrational spectroscopy-A powerful tool for the rapid identification of microbial cells at the single-cell level

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