期刊
FRONTIERS IN MICROBIOLOGY
卷 11, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fmicb.2020.616971
关键词
lung disease (diagnosis); respiratory tract infection; diagnostic test; artificial intelligence; rapid test
类别
资金
- INSERM
- CNRS
- Universite de Paris
- DGA/AID (Delegation Generale a l'Armement/Agence de l'innovation de defense)
- l'Agence Nationale de la Recherche [ANR-15-CE15-0017 StopBugEntry]
Bacterial acute pneumonia is responsible for an extremely large burden of death worldwide and diagnosis is paramount in the management of patients. While multidrug-resistant bacteria is one of the biggest health threats in the coming decades, clinicians urgently need access to novel diagnostic technologies. In this review, we will first present the already existing and largely used techniques that allow identifying pathogen-associated pneumonia. Then, we will discuss the latest and most promising technological advances that are based on connected technologies (artificial intelligence-based and Omics-based) or rapid tests, to improve the management of lung infections caused by pathogenic bacteria. We also aim to highlight the mutual benefits of fundamental and clinical studies for a better understanding of lung infections and their more efficient diagnostic management.
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