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Insight into metastatic oral cancer tissue from novel analyses using FTIR spectroscopy and aperture IR-SNOM
A novel machine learning algorithm is shown to accurately discriminate between oral squamous cell carcinoma (OSCC) nodal metastases and surrounding lymphoid tissue on the basis of a single metric, the ratio of Fourier transform infrared (FTIR) absorption intensities at 1252 cm(−1) and 1285 cm(−1). T...
Autores principales: | Ellis, Barnaby G., Whitley, Conor A., Al Jedani, Safaa, Smith, Caroline I., Gunning, Philip J., Harrison, Paul, Unsworth, Paul, Gardner, Peter, Shaw, Richard J., Barrett, Steve D., Triantafyllou, Asterios, Risk, Janet M., Weightman, Peter |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8311263/ https://www.ncbi.nlm.nih.gov/pubmed/34241603 http://dx.doi.org/10.1039/d1an00922b |
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