| Literature DB >> 33362754 |
Héloïse Rytter1,2,3, Anne Jamet1,2,3,4, Mathieu Coureuil1,2,3, Alain Charbit1,2,3, Elodie Ramond1,2,3.
Abstract
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.Entities:
Keywords: artificial intelligence; diagnostic test; lung disease (diagnosis); rapid test; respiratory tract infection
Year: 2020 PMID: 33362754 PMCID: PMC7758241 DOI: 10.3389/fmicb.2020.616971
Source DB: PubMed Journal: Front Microbiol ISSN: 1664-302X Impact factor: 5.640