Metric-based analysis of FTIR data to discriminate tissue types in oral cancer

A machine learning algorithm (MLA) has predicted the prognosis of oral potentially malignant lesions and discriminated between lymph node tissue and metastatic oral squamous cell carcinoma (OSCC). The MLA analyses metrics, which are ratios of Fourier transform infrared absorbances, and identifies ke...

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Detalles Bibliográficos
Autores principales: Ellis, Barnaby G., Ingham, James, Whitley, Conor A., Al Jedani, Safaa, Gunning, Philip J., Gardner, Peter, Shaw, Richard J., Barrett, Steve D., Triantafyllou, Asterios, Risk, Janet M., Smith, Caroline I., Weightman, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2023
Materias:
Chemistry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10152457/
https://www.ncbi.nlm.nih.gov/pubmed/37067098
http://dx.doi.org/10.1039/d3an00258f

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10152457/
https://www.ncbi.nlm.nih.gov/pubmed/37067098
http://dx.doi.org/10.1039/d3an00258f

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