| Autor: |
James Ingham, Caroline I Smith, Barnaby G Ellis, Conor A Whitley, Asterios Triantafyllou, Philip J Gunning, Steve D Barrett, Peter Gardener, Richard J Shaw, Janet M Risk, Peter Weightman |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
IOP SciNotes. 3(3) |
| ISSN: |
2633-1357 |
| Popis: |
A machine learning algorithm (MLA) has been applied to a Fourier transform infrared spectroscopy (FTIR) dataset previously analysed with a principal component analysis (PCA) linear discriminant analysis (LDA) model. This comparison has confirmed the robustness of FTIR as a prognostic tool for oral epithelial dysplasia (OED). The MLA is able to predict malignancy with a sensitivity of 84 ± 3% and a specificity of 79 ± 3%. It provides key wavenumbers that will be important for the development of devices that can be used for improved prognosis of OED. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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