Podstrona: Publikacje / Wizytówka pracownika PRz

Kusy M.: “Metodyki i techniki programowania - laboratorium” (materiały pomocnicze), Oficyna Wydawnicza Politechniki Rzeszowskiej, Rzeszów 2009

Kusy M.: “System for Cancer Diagnosis Based on Support Vector Machines and Neural Networks” (in English, PhD Thesis), Warsaw University of Technology, Faculty of Mechatronics, Warsaw 2008

Obrzut B., Kusy M., Semczuk A., Obrzut M, Kluska J.: "Prediction of 10-year Overall Survival in Patients with Operable Cervical Cancer using a Probabilistic Neural Network", Journal of Cancer.  Vol. 10, nr 18, s. 4189-4195, 2019, DOI: 10.7150/jca.33945

Kusy M.: "Fuzzy C--Means-Based Architecture Reduction of a Probabilistic Neural Network", Neural Networks. Vol. 108, s. 20-32, 2018 (DOI: 10.1016/j.neunet.2018.0 7.012)

Kusy M., Kowalski P.A.: “Weighted Probabilistic Neural Network”, Information Sciences. Vol. 430-431, s. 65-76, 2018 (DOI: 10.1016/j.ins.2017.11.036)

Kowalski P.A., Kusy M.: “Sensitivity Analysis for Probabilistic Neural Network Structure Reduction”, IEEE Transactions on Neural Networks and Learning Systems. Vol. 29, nr 5, s. 1919-1932, 2018, DOI: 10.1109/TNNLS.2017.2688482

Hanus R., Zych M., Kusy M., Jaszczur M., Petryka L.: “Identification of liquid-gas flow regime in a pipeline using gamma-ray absorption technique and computational intelligence methods”, Flow Measurement and Instrumentation. Vol. 60, s. 17-23, 2018 (DOI: 10.1016/j.flowmeasinst.2018.02.008)

Kowalski P.A., Kusy M.: “Determining significance of input neurons for probabilistic neural network by sensitivity analysis procedure”, Computational Intelligence. Vol. 34, nr 3, s. 895-916, 2018 (DOI: 10.1111/coin.12149)

Hanus R., Zych M., Kusy M., Hanus P.: “Zastosowanie absorpcji promieniowania gamma i wybranych metod sztucznej inteligencji do identyfikacji struktury przepływu ciecz-gaz w rurociągu”, Przegląd Elektrotechniczny. R. 94, nr 8, s. 146-149, 2018 (DOI: 10.15199/48. 2018.08.34)

Obrzut B., Kusy M., Semczuk A., Obrzut M., Kluska J.: “Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods”, BMC Cancer. Vol. 17, nr 1, s. 840, 2017, (DOI: 10.1186/s12885-017-3806-3)

Kusy M., Kluska J.: “Assessment of prediction ability for reduced probabilistic neural network in data classification problems”, Soft Computing. Vol. 21, nr 1, s. 199–212, 2017 (DOI: 10.1007/s00500-016-2382-9)

Kusy M., Zajdel R.: “Application of Reinforcement Learning Algorithms for the Adaptive Computation of the Smoothing Parameter for Probabilistic Neural Network”, IEEE Transactions on Neural Networks and Learning Systems. Vol. 26, nr 9, s. 2163–2175, 2015 (DOI: 10.1109/TNNLS.2014.2376703)

Kusy M.: “Dimensionality Reduction for Probabilistic Neural Network in Medical Data Classification Problems”, International Journal Of Electronics and Telecommunications. Vol. 61, nr 3, s. 293–304, 2015 (DOI: 10.1515/eletel-2015-0038)

Kusy M., Zajdel R.: “Probabilistic neural network training procedure based on Q(0)-learning algorithm in medical data classification”, Applied Intelligence. Vol. 41, nr 3, s. 837–854, 2014 (DOI: 10.1007/ s10489-014-0562-9)

Kusy M., Obrzut B., Kluska J.: “Application of gene expression programming and neural networks to predict adverse events of radical hysterectomy in cervical cancer patients”, Medical & Biological Engineering & Computing. Vol. 51, nr 12, s. 1357–1365, 2013 (DOI: 10.1007/s11517-013-1108-8)

Kusy M., Szczepanski D.: “Influence of graphical weights’ interpretation and filtration algorithms on generalization ability of neural networks applied to digit recognition”, Neural Computing & Applications. Vol. 21, nr 7, s. 1783–1790, 2012 (DOI: 10.1007/s00521-011-0754-8)

Zajdel R., Kusy  M.: "Application of Reinforcement Learning to Stacked Autoencoder Deep Network Architecture Optimization", Lecture Notes in Artificial Intelligence LNAI 10841 (L. Rutkowski, R. Scherer, M. Korytkowski, W. Pedrycz, R. Tadeusiewicz, J. Zurada, Eds), Springer International Publishing AG, s. 267-276, Part I, 2018

Kusy  M., Zajdel R.: "Probabilistic Neural Network Training Procedure with the Use of SARSA Algorithm", Lecture Notes in Artificial Intelligence LNAI 9119 (L. Rutkowski, M. Korytkowski, R. Sherer, R. Tadeusiewicz, L.A. Zadeh, J. Żurada, Eds.), Springer International Publishing Switzerland, s. 49-58, Part I, 2015

Żabiński T., Mączka T., Kluska J., Kusy M., Gierlak P., Hanus R., Prucnal S., Sęp J: "CNC Milling Tool Head Imbalance Prediction Using Computational Intelligence Methods", Lecture Notes in Artificial Intelligence LNAI 9119 (L. Rutkowski, M. Korytkowski, R. Sherer, R. Tadeusiewicz, L.A. Zadeh, J. Żurada, Eds.), Springer International Publishing Switzerland, s. 503-514, Part I, 2015

Kluska J., Kusy  M., Obrzut B.: "The Classifier for Prediction of Peri-operative Complications in Cervical Cancer Treatment", Lecture Notes in Artificial Intelligence LNAI 8468 (L. Rutkowski, M. Korytkowski, R. Sherer, R. Tadeusiewicz, L.A. Zadeh, J. Żurada, Eds.), Springer International Publishing Switzerland, s. 155-166, Part II, 2014

Żabiński T., Mączka T., Kluska J., Kusy M., Hajduk Z., Prucnal S.: "Failures Prediction in the Cold Forging Process Using Machine Learning Methods", Lecture Notes in Artificial Intelligence LNAI 8467 (L. Rutkowski, M. Korytkowski, R. Sherer, R. Tadeusiewicz, L.A. Zadeh, J. Żurada, Eds.), Springer International Publishing Switzerland, s. 622-633, Part I, 2014

Kusy  M., Zajdel R.: "Stateless Q-Learning Algorithm for Training of Radial Basis Function Based Neural Networks in Medical Data Classification", Advances in Intelligent Systems and Computing 230 (J. Korbicz, M. Kowal, Eds.) Springer-Verlag Berlin, Heiderberg, s. 267-278, 2014

Kusy  M., Kluska J.: "Probabilistic Neural Network Structure Reduction for Medical Data Classification", Lecture Notes in Artificial Intelligence LNAI 7894 (L. Rutkowski, M. Korytkowski, R. Sherer, R. Tadeusiewicz, L.A. Zadeh, J. Żurada, Eds.), Springer-Verlag Berlin, Heiderberg, s. 118-129, Part I, 2013

Kluska J., Kusy  M., Obrzut B.: "Prediction of Radical Hysterectomy Complications for Cervical Cancer Using Computational Intelligence Methods", Lecture Notes in Artificial Intelligence LNAI 7268 (L. Rutkowski, M. Korytkowski, R. Sherer, R. Tadeusiewicz, L.A. Zadeh, J. Żurada, Eds.), Springer-Verlag Berlin, Heiderberg, s. 259-267, Part II, 2012 

Kusy M.: “New Stopping Procedure for SMO Algorithm Presented in Medical Data Classification” Computational Intelligence: Methods and Applications, (A. Cader, L. Rutkowski, R. Tadeusiewicz, J. Żurada, Eds.), Academic Publishing House EXIT, s. 279-290, Warszawa 2008

Kusy M., Zajdel R.: “Prediction Capabilities of Nonlinear Models in Normalized Medical Data Classification”, Artificial Intelligence and Soft Computing (A. Cader, L. Rutkowski, R. Tadeusiewicz, J. Żurada, Eds.), Academic Publishing House EXIT, s. 267-272, Warszawa 2006

Kusy M.: “Application of SVM to ovarian classification problem”, Lecture Notes in Artificial Intelligence LNAI, 3070 (L. Rutkowski, J. Siekmann, R. Tadeusiewicz, L.A. Zadeh, Eds.), Springer-Verlag Berlin Heiderberg New York, s. 1020-1025, 2004

Kusy  M.: "Selection of Pattern Neurons for a Probabilistic Neural Network by Means of Clustering and Nearest Neighbor Techniques". Proceedings of the 6th International Conference on Control, Decision and Information Technologies, s. 598–603, IEEE. April 23–26, Paris, France, 2019 (DOI: 10.1109/CoDIT.2019.8820385)

Kowalski P. A., Kusy  M.: "Determining the significance of features with the use of Sobol method in probabilistic neural network classification tasks". Proceedings of the Federated Conference on Computer Science and Information Systems. ACSIS Vol. 11, s. 39–48, IEEE. September 3–6, Prague, Czech Republic, 2017 (DOI: 10.15439/2017F225)

Kusy  M., Kowalski P. A. "Modification of the Probabilistic Neural Network with the Use of Sensitivity Analysis Procedure". Proceedings of the Federated Conference on Computer Science and Information Systems. ACSIS Vol. 8, s. 97–103, IEEE. September 11–14, Gdansk, Poland, 2016 (DOI: 10.15439/2016F280)

Kusy M.: "Application of data classifiers to breast cancer diagnosis". The 8th Conference on Diagnostics of Processes and Systems DPS 2007. Słubice (cdrom - 8 stron), 2007

Kusy M., Zajdel R.: “Comparison of two radial function based models: Support vector machine and neural network in the classification of ovarian cancer data”. International Symposium on Innovations in Intelligent Systems and Applications, s. 316–320. June 15-18, Istambul, Turkey 2005

Kusy M.: “Computational modification of SMO algorithm in the classification of ovarian cancer data”, Akademia Górniczo-Hutnicza Konferencja Sztuczna Inteligencja w Inżynierii Biomedycznej SIIB. AGH Kraków, Kraków (cdrom - 4 strony), 2004