How Raman spectroscopy and AI are used to support skin cancer screening — principle, method, explainability, data and publications. Presented honestly for the research stage.
When a 785nm laser illuminates skin tissue, most scattered light keeps its wavelength; a tiny fraction shifts with molecular bond vibrations (Raman scattering). The resulting spectrum is a biochemical fingerprint of the tissue.
Biochemical changes from cancer cells (proteins, lipids, DNA…) alter intensity at certain wavenumbers. This is the signal the AI learns to estimate a risk indicator — non-invasive, no tissue sampling.
Illustrative Raman spectrum (not patient data). Orange lines: the 8 wavenumbers the AI relies on most (XAI).
A signal-processing + machine-learning pipeline, designed to be lightweight and run on-device (offline).
Savitzky–Golay smoothing + SNV normalization to remove noise and baseline drift.
PCA (50 components) compresses the 1501-point spectrum, keeping most variance.
Random Forest (400 trees) into 4 classes: BCC · SCC · Melanoma · Benign.
Exported to ONNX (~3.4 MB) for lightweight, offline on-device inference.
Instead of a black box, ZinMed traces the wavenumbers (cm⁻¹) the model attends to most, which map to known biochemical bonds. This is a core differentiator versus giving only a number.
The model-development set contains ~1,200 Raman spectra — ~500 measured from clinical samples and ~700 simulated — used for internal training and testing. Composition is as declared by the research group; not independently validated.
Design target: 75–85% sensitivity and specificity. This is a research goal, not a clinically validated result.
Designed toward Class 1 laser safety (IEC 60825) and medical electrical safety (IEC 60601) — under evaluation.
Building a quality-management system aligned to ISO 13485 (not yet certified).
The team has a substantial publication record in Raman + AI for biomedical diagnosis (diabetes, cancer, devices). A selection below.
Are you a clinician, researcher or health facility wanting to help validate this technology? Get in touch.
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