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Khan S.,National Institute for Lasers and Optronics NILOP | Ullah R.,National Institute for Lasers and Optronics NILOP | Saleem M.,National Institute for Lasers and Optronics NILOP | Bilal M.,National Institute for Lasers and Optronics NILOP | And 4 more authors.
Optik | Year: 2016

We are presenting Raman spectroscopic analysis of dengue virus infection in the human blood sera. Blood samples from 40 individuals infected with dengue virus and 25 healthy volunteers have been used in this study. Raman spectra of all these samples have been acquired in the spectral range from 600 cm-1 to 1750 cm-1 using 532 nm laser as an excitation source. These Raman spectra have been used to analyze the biochemical changes appeared in the blood caused by dengue virus infection. Two Raman lines at 750 cm-1 and 850 cm-1 found in all spectra of dengue infected sera, indicate the presence of adenosine diphosphate (ADP), which is expected to be excreted due to rupturing of thrombocytes. © 2015 Elsevier GmbH. Source


Khan S.,National Institute for Lasers and Optronics NILOP | Ullah R.,National Institute for Lasers and Optronics NILOP | Khan A.,Applied Recognition | Wahab N.,Applied Recognition | And 2 more authors.
Biomedical Optics Express | Year: 2016

The current study presents the use of Raman spectroscopy combined with support vector machine (SVM) for the classification of dengue suspected human blood sera. Raman spectra for 84 clinically dengue suspected patients acquired from Holy Family Hospital, Rawalpindi, Pakistan, have been used in this study.The spectral differences between dengue positive and normal sera have been exploited by using effective machine learning techniques. In this regard, SVM models built on the basis of three different kernel functions including Gaussian radial basis function (RBF), polynomial function and linear functionhave been employed to classify the human blood sera based on features obtained from Raman Spectra.The classification model have been evaluated with the 10- fold cross validation method. In the present study, the best performance has been achieved for the polynomial kernel of order 1. A diagnostic accuracy of about 85% with the precision of 90%, sensitivity of 73% and specificity of 93% has been achieved under these conditions. © 2016 Optical Society of America. Source

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