SERS nanowire chip and machine learning enabled instant identification and classification of clinically relevant wild-type and antibiotic resistant bacteria at species and strain level

Authors

Sathi Das

Published

January 13, 2023

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DOI

10.1101/2023.01.12.523744

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SERS nanowire chip and machine learning enabled instant identification and classification of clinically relevant wild-type and antibiotic resistant bacteria at species and strain level

Authors

Sathi Das

Published

January 13, 2023

Add a comment...

Supporters

Support the authors with ResearchCoin

Preprint Server

Topics

DOI

10.1101/2023.01.12.523744

License

cc-no

Supporters

Support the authors with ResearchCoin

Preprint Server

Topics

DOI

10.1101/2023.01.12.523744

License

cc-no

Paper

Paper

Paper

Paper

SERS nanowire chip and machine learning enabled instant identification and classification of clinically relevant wild-type and antibiotic resistant bacteria at species and strain level

Supporters

Preprint Server

Topics

DOI

License

SERS nanowire chip and machine learning enabled instant identification and classification of clinically relevant wild-type and antibiotic resistant bacteria at species and strain level

Supporters

Preprint Server

Topics

DOI

License

Supporters

Preprint Server

Topics

DOI

License