A unified machine learning framework for oral cancer classification using Raman spectra from tissue, serum, and urine.
Raman spectroscopy has emerged as a promising label-free technique for cancer detection; however, variability across biological sample types and the limited availability of complete multi-source data per patient present challenges for developing generalisable classification models. This study proposes a unified machine...