Using artificial intelligence to reduce diagnostic workload without compromising detection of urinary tract infections

BACKGROUND: A substantial proportion of microbiological screening in diagnostic laboratories is due to suspected urinary tract infections (UTIs), yet approximately two thirds of urine samples typically yield negative culture results. By reducing the number of query samples to be cultured and enablin...

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Detalles Bibliográficos
Autores principales: Burton, Ross J., Albur, Mahableshwar, Eberl, Matthias, Cuff, Simone M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6708133/
https://www.ncbi.nlm.nih.gov/pubmed/31443706
http://dx.doi.org/10.1186/s12911-019-0878-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6708133/
https://www.ncbi.nlm.nih.gov/pubmed/31443706
http://dx.doi.org/10.1186/s12911-019-0878-9

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