Rapid bacterial identification through volatile organic compound analysis and deep learning
This work provides a new approach to quickly identify bacterial microorganisms. Using this method can automatically identify bacteria in GC-IMS detection results, helping clinical doctors quickly detect bacterial species, accurately prescribe medication, thereby controlling epidemics, and minimizing the negative impact of bacterial resistance on society.
Authors
- Lin Zeng (ORCID: https://orcid.org/0000-0001-8707-5854)
- Bangfu Zhou
- Bowen Yan (ORCID: https://orcid.org/0000-0001-7854-3142)
- Weiping Lu (ORCID: https://orcid.org/0000-0002-4424-5152)
- Min Li (ORCID: https://orcid.org/0000-0002-7113-2700)
- Qinghua He (ORCID: https://orcid.org/0000-0003-2091-8321)
- Yanyi Lu
Institutions
- Army Medical University (CN)
- Daping Hospital (CN)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2024-11-06
- DOI
- https://doi.org/10.1186/s12859-024-05967-4
- Citations
- 3
- Primary Topic
- Advanced Chemical Sensor Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.55
Funders
- Chongqing Municipal Health Commission
- Chongqing Municipal Public Health Bureau, Chongqing People's Municipal Government