Analysis of tuberculosis disease through Raman spectroscopy and machine learning

Published 2018

Aftab Ahmad Khan COMSAT Institute of Information Technology Abbottabta

Dr. Muhammad Bilal National Institute of Lasers and Optronics, Nilore, Islamabad, Pakistan

DOI: 10.1016/j.pdpdt.2018.10.014

Abstract:

We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from tuberculosis patients. Blood samples of 60 patients have confirmed active pulmonary tuberculosis and 14 samples of healthy age matched control were used in the current study. Spectra from entire sera samples were acquired using 785 nm laser Raman system. Support Vector Machine (SVM) together with Principal Component Analysis (PCA) has been used for highlighting variations...

Excerpt:

An integrated system also has a microscope (RSM - 785, Agiltron) for viewing the sample. An objective lens having numerical aper ture of 0.25 was used for tight focusing of laser beam onto the sample surface. In - elastically scattered Raman light was also collected though same objective...