G. Stylios

Work place: Technological Educational Institute of the Ionian Islands, Department of Business Administration, Lefkada Greece

E-mail: gstylios@teiion.gr


Research Interests: Data Mining, Data Structures and Algorithms


Mr. George Stylios received his diploma at Physics from the Aristotle University of Thessaloniki in 1994 and his MSc in Information Systems & Technology from the City University, London, in 2002. Currently he works as a Lecturer at the Technical Educational Institute of Ionian Islands, Department of Information Technology Applications in Management and Economics, Lefkada, Greece and he is head of the department. He is a PhD student at the Databases Laboratory, Department of Computer Engineering & Informatics of the University of Patras. His research interests include: E-government, data mining, digital citizen, e-citizen; processing data from web forums, blogs, public consultation to parse texts and opinion mining; data mining algorithms within the procedure to support business decisions; web mining. He has published numerous articles in international scientific journals and conference.

Author Articles
Using Artificial Immune Recognition Systems in Order to Detect Early Breast Cancer

By C.D. Katsis I. Gkogkou C.A. Papadopoulos Y. Goletsis P.V. Boufounou G. Stylios

DOI: https://doi.org/10.5815/ijisa.2013.02.04, Pub. Date: 8 Jan. 2013

In this work, a decision support system for early breast cancer detection is presented. In hard to diagnose cases, different examinations (i.e. mammography, ultrasonography and magnetic resonance imaging) provide contradictory findings and patient is guided to biopsy for definite results. The proposed method employs a Correlation Feature Selection procedure and an Artificial Immune Recognition System (AIRS) and is evaluated using real data collected from 53 subjects with contradictory diagnoses. Comparative results with commonly used artificial intelligence classifiers verify the suitability of the AIRS classifier. The application of such an approach can reduce the number of unnecessary biopsies.

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