SERS-AI-LUA-Driven Salivary Diagnosis of Head and Neck Cancer Using Graphene-Assisted Plasmonic Nanocorals.

ABSTRACT: The early detection of head and neck cancer (HNC) remains an important challenge owing to the lack of reliable noninvasive biomarkers. This study introduces a graphene-assisted plasmonic nanocoral platform coupled with an artificial intelligence-linear unmixing algorithm for diagnosing HNC from saliva and identifying associated metabolic biomarkers. The nanocoral structures, formed via a spontaneous gold growth mechanism on graphene templates, exhibit strong plasmonic enhancement and selective adsorption of volatile metabolites. Raman signals acquired from the saliva of HNC patients and healthy individuals are analyzed using a logistic regression model, achieving 98% classification accuracy. To identify potential metabolic biomarkers, candidate metabolites are initially selected based on s

SUBMITTER: Seo HJ 

PROVIDER: S-EPMC12752647 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature