Artificial intelligence-aided rapid and accurate identification of clinical fungal infections by single-cell Raman spectroscopy

Integrating artificial intelligence and new diagnostic platforms into routine clinical microbiology laboratory procedures has grown increasingly intriguing, holding promises of reducing turnaround time and cost and maximizing efficiency. At least one billion people are suffering from fungal infectio...

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Detalles Bibliográficos
Autores principales: Xu, Jiabao, Luo, Yanjun, Wang, Jingkai, Tu, Weiming, Yi, Xiaofei, Xu, Xiaogang, Song, Yizhi, Tang, Yuguo, Hua, Xiaoting, Yu, Yunsong, Yin, Huabing, Yang, Qiwen, Huang, Wei E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Microbiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073597/
https://www.ncbi.nlm.nih.gov/pubmed/37032865
http://dx.doi.org/10.3389/fmicb.2023.1125676

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073597/
https://www.ncbi.nlm.nih.gov/pubmed/37032865
http://dx.doi.org/10.3389/fmicb.2023.1125676

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