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Multi-target fluorescence staining of bacteria smears enables rapid machine learning-assisted species classification

Maxence Galvan Michael Fujarski Can Beslendi Frieder Schaumburg Julian Varghese Johannes Liesche

mLife2026，Vol.5Issue(2)：P.229-238,10.

mLife2026，Vol.5Issue(2)：P.229-238,10.DOI:10.1002/mlf2.70076

Multi-target fluorescence staining of bacteria smears enables rapid machine learning-assisted species classification

Maxence Galvan ¹Michael Fujarski ²Can Beslendi ²Frieder Schaumburg ¹Julian Varghese ³Johannes Liesche⁴

作者信息

1. Institute of Medical Microbiology,University Hospital Munster,Munster,Germany
2. Institute of Medical Informatics,University of Munster,Munster,Germany
3. Institute of Medical Informatics,University of Munster,Munster,Germany Institute of Medical Informatics,Otto-von-Guericke University Magdeburg,Magdeburg,Germany
4. Institute of Medical Microbiology,University Hospital Munster,Munster,Germany Institute of Biology,University of Graz,Graz,Austria
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摘要

关键词

artificial intelligence(AI)/bloodstream infection/fluorescence microscopy/rapid diagnostics/resource-limited settings

分类

医药卫生

引用本文复制引用

Maxence Galvan,Michael Fujarski,Can Beslendi,Frieder Schaumburg,Julian Varghese,Johannes Liesche..Multi-target fluorescence staining of bacteria smears enables rapid machine learning-assisted species classification[J].mLife,2026,5(2):P.229-238,10.

基金项目

supported by funds from the“Deutsche Gesellschaft fur Internationale Zusammenarbeit-Klinikpartnerschaften”(81281918) （81281918）

the Open Access Publication Fund of the University of Graz （）

Open Access funding provided by Universitat Graz/KEMO. （）

mLife

ISSN：2097-1699

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