Bioinformatics of lung cancerBioinformatics of lung cancer Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2015-10-252015enThe objective of this study is to explore novel bioinformatics techniques, namely, the Polarimetric Exploratory Data Analysis (pEDA), for early identification and discrimination of precancerous and cancerous lung tissues. The outcome of this study indicates that the full-width-at half maximum (FWHM) and Dynamic Range (DR) extracted from histograms of inherent (label-free) near infrared (NIR) diffused-polarimetric reflectance signals provide an important metrics for the characterization of cancerous tissue. Application of pEDA on the acquired data has been proved an effective diagnostic tool aimed at discriminating optical information among normal, precancerous, and cancerous lung tissue samples. Therefore, it can eventually be proved a useful diagnostic tool in the early detection of Non-Small Cell Lung Cancer (NSCLC) as well as in classical cytopathology and histopathology.http://creativecommons.org/licenses/by/4.0/1-6 IEEE International Conference on Imaging Systems and Techniques (IST) Stefanie Marotta Zervakis Michalis Ζερβακης Μιχαλης Aditi Deshpande Sarhan Musa Livanos, Georges Ying Na Tannaz Farrahi Institute of Electrical and Electronics Engineers Basic medical sciences Basic sciences, Medical Biomedical sciences Health sciences Preclinical sciences Sciences, Medical medical sciences basic medical sciences basic sciences medical biomedical sciences health sciences preclinical sciences sciences medical