Principal component analysis and artificial neural network analysis of oral tissue fluorescence spectra: classification of normal premalignant and malignant pathological conditions.
about
Predicting recurrent aphthous ulceration using genetic algorithms-optimized neural networks.Raman spectra exploring breast tissues: comparison of principal component analysis and support vector machine-recursive feature elimination.Model-based spectroscopic analysis of the oral cavity: impact of anatomy.
P2860
Principal component analysis and artificial neural network analysis of oral tissue fluorescence spectra: classification of normal premalignant and malignant pathological conditions.
description
2006 nî lūn-bûn
@nan
2006 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2006 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2006年の論文
@ja
2006年論文
@yue
2006年論文
@zh-hant
2006年論文
@zh-hk
2006年論文
@zh-mo
2006年論文
@zh-tw
2006年论文
@wuu
name
Principal component analysis a ...... gnant pathological conditions.
@ast
Principal component analysis a ...... gnant pathological conditions.
@en
type
label
Principal component analysis a ...... gnant pathological conditions.
@ast
Principal component analysis a ...... gnant pathological conditions.
@en
prefLabel
Principal component analysis a ...... gnant pathological conditions.
@ast
Principal component analysis a ...... gnant pathological conditions.
@en
P2093
P2860
P356
P1433
P1476
Principal component analysis a ...... gnant pathological conditions.
@en
P2093
Arindam Sarkar
B R Krishnanand
C Santhosh
Jacob Kurien
K K Mahato
Lawrence D'Almeida
Satadru Ray
V B Kartha
P2860
P304
P356
10.1002/BIP.20473
P577
2006-06-01T00:00:00Z