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Artificial Intelligence Laboratory Head: akad. prof. dr. Ivan Bratko Team Prof. dr. Ivan Bratko Tadej Janež dr. Aleksander Sadikov Vida Groznik dr. Jure Žabkar Aljaž Košmerlj Artificial Intelligence Laboratory dr. Martin Možina dr. Matej Guid Current projects/research • Cognitive Robotics • Machine Learning for Building Intelligent Tutoring Systems • Molecular and Other Prognosticators of Lung Cancer and Mesothelioma • GuruCue: Recommender Systems • 3R Tim: Optimization of Warehouse Logistics Artificial Intelligence Laboratory Autonomous discovery of concepts • Košmerlj, A., Bratko, I., Žabkar, J.: Embodied concept discovery through qualitative action models. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS) • Leban, G., Žabkar, J., Bratko, I.: An Experiment in Robot Discovery with ILP. In: Proceedings of the eighteenth International Conference on Inductive Logic Programming (ILP) Artificial Intelligence Laboratory Learning in a complex environment • Janež, T., Žabkar, J., Možina, M., Bratko, I.: It may be faster to learn in a more complex environment. Sent to: Journal of Autonomous Agents and Multi-Agent Systems Artificial Intelligence Laboratory Machine Learning for Building Intelligent Tutoring Systems • Partner: Department of Neurology, University Medical Centre, Ljubljana • ITS for: – symbolic problem-solving domains (chess, tremor diagnosis) – motor skill domains (walking in patients – multiple sclerosis) • • Groznik, V., Guid, M., Sadikov, A., Možina, M., Georgiev, D., Kragelj, V., Ribarič, S., Pirtošek, Z., Bratko, I.. Elicitation of neurological knowledge with ABML. Invited to: Artificial Intelligence in Medicine. Sadikov, A., Možina, M., Guid, M., Krivec, J., Bratko, I. Automated chess tutor. Lect. notes comput. sci., str. 13-25, 2007 Artificial Intelligence Laboratory Molecular and Other Prognosticators of Lung Cancer and Mesothelioma • Partner: University Clinic of Respiratory and Allergic Diseases, Golnik • Data analysis • Help with experimental design setup • Designing a tool for survival estimation based on individual patient’s characteristics (clinico-pathological data and new markers) • • • Borštnar, S., Sadikov, A., Možina, B., Čufer, T. High levels of uPA and PAI-1 predict a good response to anthracyclines. Breast cancer res. treat., 2010, vol. 121, no. 3, pgs. 615-624 Ovčariček, T., Triller, N., Sadikov, A., Čufer, T. Prognostic value of C-reactive protein and other classical factors in patients with advanced non-small cell lung carcinoma treated in routine clinical practice. Zdrav Vestn, 2010, vol. 79, no. 10, str. 669-676 Golouh, R., Čufer, T., Sadikov, A., Nussdorfer, P. The prognostic value of Stathmin-1, S100A2, and SYK proteins in ER-positive primary breast cancer patients treated with adjuvant tamoxifen monotherapy : an immunohistochemical study. Breast cancer res. treat., Jul. 2008, vol. 110, no. 2, str. 317-326 Artificial Intelligence Laboratory GuruCue: Recommender System Artificial Intelligence Laboratory Artificial Intelligence Laboratory