Deep Learning-Assisted Rapid Bacterial Classification Based on Raman Spectroscopy of Bacteria Lysed by Acoustically Driven Fiber-Tip Vibration.

ABSTRACT: Rapid and accurate identification of bacterial pathogens is critical for effective clinical decision-making and combating antibiotic resistance. Surface-enhanced Raman spectroscopy (SERS) combined with machine learning (ML) offers a powerful method for rapid, label-free bacterial identification. Conventional methods rely on surface molecular structures for identification, yet the richer and unique spectral information from intracellular biomolecules is often masked by the bacterial envelope, limiting classification accuracy. Here, a novel bacterial classification method is demonstrated by introducing acoustofluidic lysis based on the vibrating fiber-tip, combined with Raman spectroscopy and deep learning. The fiber-tip oscillates in a torsional mode, generating a controlled single-vortex w

SUBMITTER: Liu Y 

PROVIDER: S-EPMC12407356 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature