Machine learning-driven electronic identifications of single pathogenic bacteria

A rapid method for screening pathogens can revolutionize health care by enabling infection control through medication before symptom. Here we report on label-free single-cell identifications of clinically-important pathogenic bacteria by using a polymer-integrated low thickness-to-diameter aspect ra...

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Detalles Bibliográficos
Autores principales: Hattori, Shota, Sekido, Rintaro, Leong, Iat Wai, Tsutsui, Makusu, Arima, Akihide, Tanaka, Masayoshi, Yokota, Kazumichi, Washio, Takashi, Kawai, Tomoji, Okochi, Mina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512020/
https://www.ncbi.nlm.nih.gov/pubmed/32968098
http://dx.doi.org/10.1038/s41598-020-72508-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512020/
https://www.ncbi.nlm.nih.gov/pubmed/32968098
http://dx.doi.org/10.1038/s41598-020-72508-3

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