Differentiating smokers and nonsmokers based on Raman spectroscopy of oral fluid and advanced statistics for forensic applications |
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Authors: | Entesar Al‐Hetlani,Lenka Hal mkov ,Mohamed O. Amin,Igor K. Lednev |
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Affiliation: | Entesar Al‐Hetlani,Lenka Halámková,Mohamed O. Amin,Igor K. Lednev |
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Abstract: | Raman spectroscopy has proven to be a valuable tool for analyzing various types of forensic evidence such as traces of body fluids. In this work, Raman spectroscopy was employed as a nondestructive technique for the analysis of dry traces of oral fluid to differentiate between smoker and nonsmoker donors with the aid of advanced statistical tools. A total of 32 oral fluid samples were collected from donors of differing gender, age and race and were subjected to Raman spectroscopic analysis. A genetic algorithm was used to determine eight spectral regions that contribute the most to the differentiation of smokers and nonsmokers. Thereafter, a classification model was developed based on the artificial neural network that showed 100% accuracy after external validation. The developed approach demonstrates great potential for the differentiation of smokers and nonsmokers based on the analysis of dry traces of oral fluid. |
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Keywords: | artificial neural networks forensics nonsmoker oral fluid Raman spectroscopy smoker statistics |
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