Vibrational spectroscopy and artificial intelligence for dynamic phenotypic characterization of antimicrobial resistance
- DOI
- 10.3389/fcimb.2026.1927600
- Published
- 2026-10-21
- Container
- Frontiers in Cellular and Infection Microbiology
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fcimb.2026.1927600,
title = {Vibrational spectroscopy and artificial intelligence for dynamic phenotypic characterization of antimicrobial resistance},
author = {Claudia P. Barrera Patiño and Jennifer M. Soares and Kate C. Blanco and Vanderlei S. Bagnato},
year = {2026},
journal = {Frontiers in Cellular and Infection Microbiology},
doi = {10.3389/fcimb.2026.1927600},
url = {https://doi.org/10.3389/fcimb.2026.1927600}
}RIS
TY - JOUR TI - Vibrational spectroscopy and artificial intelligence for dynamic phenotypic characterization of antimicrobial resistance AU - Claudia P. Barrera Patiño AU - Jennifer M. Soares AU - Kate C. Blanco AU - Vanderlei S. Bagnato PY - 2026 JO - Frontiers in Cellular and Infection Microbiology DO - 10.3389/fcimb.2026.1927600 UR - https://doi.org/10.3389/fcimb.2026.1927600 ER -
APA
Patiño, C. P. B., Soares, J. M., Blanco, K. C., & Bagnato, V. S. (2026). Vibrational spectroscopy and artificial intelligence for dynamic phenotypic characterization of antimicrobial resistance. Frontiers in Cellular and Infection Microbiology. https://doi.org/10.3389/fcimb.2026.1927600
Source records
- crossref · retrieved 2026-11-06T21:47:22.304Z