Urine is considered as one of the diagnostically important bio fluids, as it has many metabolites. The distribution and the physiochemical properties of the metabolites may vary during any altered metabolic and pathological conditions. Raman spectroscopy was employed in the characterization of the metabolites of human urine of normal subjects and oral cancer patients in the finger print region (500-1800 cm À1 ). Principal component analysis-based linear discriminant analysis was performed to discriminate cancer patients from normal subjects. The discriminant analysis classifies the cancer patients from normal subjects with a sensitivity and specificity of 98.6% and 87.1%, respectively, with an overall accuracy of 93.7%.
In the present study, Raman spectroscopy has been employed in the discrimination of the saliva of normal subjects from patients with oral submucous fibrosis and oral squamous cell carcinomaat 785-nm excitation. From the spectral signatures, prominent difference between normal and abnormal group because of variations in metabolic and pathological conditions of the subjects was observed. Principal component analysis coupled with linear discriminant analysis yielded a diagnostic sensitivity of 96.4 and 93.8% and a specificity of 70.2 and 95.7% in the classification of normal from premalignant and normal from malignant, respectively, confirming the efficacy of Raman spectroscopy in the classification of normal and oral abnormalities.
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