Sample Publications

2011

Pizzi NJ. Fuzzy quartile encoding as a preprocessing method for biomedical pattern classification. Theoretical Computer Science 412(42) 5909–5929.
Pizzi NJ. Mapping software metrics to module complexity: A pattern classification approach. Journal of Software Engineering and Applications 4(7) 426–432 (2011).
Pizzi NJ, Park B. Spectral classification using fuzzy feature sampling. Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society, March 18–20, El Paso, USA, 162–167 (2011).
Moghadas MS, Pizzi NJ, Wu J, Yan P, Fisman DN, Tamblyn S. Canada in the face of the 2009 H1N1 pandemic. Influenza and Other Respiratory Viruses 5(2) 83–88 (2011).
Pizzi NJ, Demko A, Pedrycz W. The analysis of software complexity using stochastic metric selection. Journal of Pattern Recognition Research 6(1) 19–31 (2011).
Mostaço-Guidolin LC, Pizzi NJ, Demko AB, Moghadas SM. A software development framework for agent-based infectious disease modelling. In: Biomedical Engineering Trends in Electronics, Communications and Software (Laskovski AN (eds.)), Rijeka: InTech 641–664 (2011).
Arino J, Bauch C, Brauer F, Driedger SM, Greer AL, Moghadas SM, Pizzi NJ, Sander B, Tuite A, van den Driessche P, Watmough J. Pandemic influenza: Modelling and public health perspectives. Molecular Biology and Evolution 8(1) 1–20 (2011).

Pizzi NJ, Pedrycz W. Aggregating multiple classification results using fuzzy integration and stochastic feature selection. International Journal of Approximate Reasoning 51 883–894 (2010).
Pedrycz W, Lee DJ, Pizzi NJ. Representation and classification of high dimensional biomedical spectral data. Pattern Analysis & Applications 13 423–436 (2010).
Pizzi NJ, Demko A, Pedrycz W. Variance analysis and biomedical pattern classification. Proceedings of the World Congress on Computational Intelligence, July 18–23, Barcelona, Spain 3296–3303 (2010).
Pizzi NJ, Demko A, Pedrycz W. Classification using an adaptive fuzzy network. Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society, July 12–14, Toronto, Canada, 41–46 (2010).

Pizzi NJ, Pedrycz W. Discriminatory components for pattern classification. Proceedings of the World Congress of the International Fuzzy Systems Association, July 19–23, Lisbon, Portugal, 748–753 (2009).
Moghadas S, Day T, Bauch C, Driedger SM, Brauer F, Greer A, Yan P, Wu J, Pizzi NJ, Fisman D. Modelling of pandemic influenza: A guide for the perplexed. Canadian Medical Association Journal 181 171–173 (2009).
Pizzi NJ, Pedrycz W. A fuzzy logic network for pattern classification. Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society, June 14–17, Cincinnati, USA, 53–58 (2009).
Pizzi NJ. Information processing in biomedical applications. In: Information Processing Human-Centric Information Processing Through Granular Modelling (Bargiela A, Pedrycz W (Eds.)). Berlin: Springer-Verlag 289–311 (2009).
Demko AB, Pizzi NJ. Scopira: An open source C++ framework for biomedical data analysis applications. Software—Practice and Experience 39 641–660 (2009).
Moghadas SM, Pizzi NJ, Wu J, Yan P. Managing public health crises: the role of models in pandemic preparedness. Influenza and Other Respiratory Viruses 3(2), 75–79 (2009).
Pedrycz W, Park BJ, Pizzi NJ. Identifying core sets of discriminatory features using particle swarm optimization. Expert Systems with Applications 36 4610–4616 (2009).

Pizzi NJ, Pedrycz W. An analysis of potentially imprecise class labels using a fuzzy similarity measure. Proceedings of the IEEE World Congress on Computational Intelligence, June 1–6, Hong Kong 667–672 (2008).
Pizzi NJ. Biomedical data analysis using dispersion-adjusted fuzzy quantile encoding. Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society, May 19–22, New York, USA, 48–53 (2008).
Pizzi NJ, Software quality prediction using fuzzy integration: a case study. Soft Computing Journal 12 67–76 (2008).

Alexiuk MD, Pizzi NJ, Pedrycz W. Tuning FCMP to elicit novel time course signatures in fMRI neural activation studies. In: Analysis and Design of Intelligent Systems Using Soft Computing Techniques (Melin P, Castillo O, Ramirez EG, Kacprzyk J, Pedrycz W (eds.)). Berlin: Springer-Verlag 746–755 (2007).
Alexiuk MD, Pizzi NJ. Robust exploratory analysis of magnetic resonance images using FCM with feature partitions. In: Advances in Fuzzy Clustering and its Applications (de Oliveira JV, Pedrycz W (eds.)). Chichester: John Wiley amp; Sons 373–391 (2007).
Wiebe C, Pizzi NJ. Reproducibility of experimental results from a highly parallelized classification algorithm. Proceedings of the IEEE Canadian Conference on Electrical and Computer Engineering, April 22–26, Vancouver, Canada, 594–597 (2007).
Pizzi NJ, Alexiuk MD, Pedrycz W. Classification of biomedical spectra using fuzzy interquartile encoding and stochastic feature selection. Proceedings of the IEEE Symposium Series on Computational Intelligence and Data Mining, April 1–5, Honolulu, USA, 668–673 (2007).
Alexiuk MD, Pizzi NJ, Pedrycz W. Intensity/correlation thresholding of fMRI data: data-driven regions of interest using bridge voxels. Proceedings of the IEEE Symposium Series on Computational Intelligence in Image and Signal Processing, April 1–5, Honolulu, USA, 194–197 (2007).

Alexiuk MA, Pizzi NJ, Sawatzky G, Pedrycz W. Captology in narrowcast advertising: a swarm simulation of persuasion models. Proceedings of the Canadian Conference on Electrical and Computer Engineering, May 7–10, Ottawa, Canada, 1692–1695 (2006).
Pizzi NJ, Pedrycz W. Predicting qualitative assessments using fuzzy aggregation. Proceedings of the North American Fuzzy Information Processing Society Conference, June 3–6, Montréal, Canada, vol. MPM3, 12–17 (2006).
Alexiuk M, Pizzi NJ, Pedrycz W. Data driven determination of global fMRI thresholds using regions of interest bridge voxels. Proceedings of the Canadian Medical and Biological Engineering Society Conference, June 1–3, Vancouver, Canada, vol. SC3, 13–16 (2006).
Pizzi NJ, Somorjai RL, Pedrycz W. Classifying biomedical spectra using stochastic feature selection and parallelized multi-layer perceptrons. In: Modern Information Processing: From Theory to Applications (Bouchon-Meunier B, Coletti G, Yager RR (eds.)). Amsterdam: Elsevier 383–393 (2006).
Pedrycz W, Breuer A, Pizzi NJ. Fuzzy adaptive logic networks as hybrid models of quantitative software engineering. Intelligent Automation and Soft Computing 12 189–209 (2006).