SVM Optimization for Brain Tumor Identification Using Infrared Spectroscopic Samples

The work presented in this paper is focused on the use of spectroscopy to identify the type of tissue of human brain samples employing support vector machine classifiers. Two different spectrometers were used to acquire infrared spectroscopic signatures in the wavenumber range between 1200–3500 cm(−...

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Detalles Bibliográficos
Autores principales: Fabelo, Himar, Ortega, Samuel, Casselden, Elizabeth, Loh, Jane, Bulstrode, Harry, Zolnourian, Ardalan, Grundy, Paul, M. Callico, Gustavo, Bulters, Diederik, Sarmiento, Roberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308411/
https://www.ncbi.nlm.nih.gov/pubmed/30567396
http://dx.doi.org/10.3390/s18124487

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308411/
https://www.ncbi.nlm.nih.gov/pubmed/30567396
http://dx.doi.org/10.3390/s18124487

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