Masaryk University

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    2024

    1. BUOSI, Samuele, Mohan TIMILSINA, Maria TORRENTE, Mariano PROVENCIO, Dirk FEY and Vít NOVÁČEK. Boosting predictive models and augmenting patient data with relevant genomic and pathway information. Computers in Biology and Medicine. Pergamon-Elsevier Science Press, 2024, vol. 2024, No 108398, p. 1-9. ISSN 0010-4825. Available from: https://dx.doi.org/10.1016/j.compbiomed.2024.108398.
    2. PROCHÁZKA, David, Terézia SLANINÁKOVÁ, Jozef ČERŇANSKÝ, Jaroslav OĽHA, Matej ANTOL and Vlastislav DOHNAL. Scaling Learned Metric Index to 100M Datasets. In Edgar Chávez, Benjamin Kimia, Jakub Lokoč, Marco Patella, Jan Sedmidubsky. 17th International Conference on Similarity Search and Applications (SISAP 2024). Cham: Springer, 2024, p. 266-273. ISBN 978-3-031-75822-5. Available from: https://dx.doi.org/10.1007/978-3-031-75823-2_22.

    2023

    1. ZELINA, Petr, Jana HALÁMKOVÁ and Vít NOVÁČEK. Extraction, labeling, clustering, and semantic mapping of segments from clinical notes. IEEE TRANSACTIONS ON NANOBIOSCIENCE. UNITED STATES: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023, vol. 22, No 4, p. 781-788. ISSN 1536-1241. Available from: https://dx.doi.org/10.1109/TNB.2023.3275195.
    2. JANIK, Adrianna, Maria TORRENTE, Luca COSTABELLO, Virginia CALVO, Brian WALSH, Carlos CAMPS, Sameh K MOHAMED, Ana L ORTEGA, Vít NOVÁČEK, Bartomeu MASSUTÍ, Pasquale MINERVINI, M Rosario GARCIA CAMPELO, Edel del BARCO, Joaquim BOSCH-BARRERA, Ernestina MENASALVAS, Mohan TIMILSINA and Mariano PROVENCIO. Machine Learning–Assisted Recurrence Prediction for Patients With Early-Stage Non–Small-Cell Lung Cancer. JCO CLINICAL CANCER INFORMATICS. UNITED STATES: LIPPINCOTT WILLIAMS & WILKINS, 2023, vol. 7, e2200062, p. 1-11. ISSN 2473-4276. Available from: https://dx.doi.org/10.1200/CCI.22.00062.

    2022

    1. TORRENTE, María, Pedro A SOUSA, Roberto HERNÁNDEZ, Mariola BLANCO, Virginia Calvo Ana COLLAZO, Gracinda R GUERREIRO, Beatriz NÚÑEZ, Joao PIMENTAO, Juan Cristóbal SÁNCHEZ, Manuel CAMPOS, Luca COSTABELLO, Vít NOVÁČEK, Ernestina MENASALVAS, María Esther VIDAL, Mariano PROVENCIO and Virginia CALVO. An Artificial Intelligence-Based Tool for Data Analysis and Prognosis in Cancer Patients: Results from the Clarify Study. CANCERS. SWITZERLAND: MDPI, 2022, vol. 14, No 16, p. 1-10. ISSN 2072-6694. Available from: https://dx.doi.org/10.3390/cancers14164041.
    2. TIMILSINA, Mohan, Vít NOVÁČEK, Mathieu DAQUIN and Haixuan YANG. Boundary heat diffusion classifier for a semi-supervised learning in a multilayer network embedding. NEURAL NETWORKS. ENGLAND: PERGAMON-ELSEVIER SCIENCE LTD, 2022, vol. 156, No 1, p. 205-217. ISSN 0893-6080. Available from: https://dx.doi.org/10.1016/j.neunet.2022.10.005.
    3. TIMILSINA, Mohan, Dirk FEY, Adrianna JANIK, Maria TORRENTE, Mariano PROVENCIO, Alberto Cruz BERMUDEZ, Enric CARCERENY, Luca COSTABELLO, Delvys Rodrıguez ABREU, Manuel COBO, Rafael Lopez CASTRO, Reyes BERNABE, Maria GUIRADO, Pasquale MINERVINI and Vít NOVÁČEK. Integration of Medical and Genomic Information to Enhance Relapse Prediction in Early Stage Lung Cancer Patients. Online. In Proceedings of the Annual Symposium of the American Medical Informatics Association. Washington, USA: AMIA, 2022, p. 1082-1091. ISSN 1559-4076.
    4. ZELINA, Petr, Jana HALÁMKOVÁ and Vít NOVÁČEK. Unsupervised extraction, labelling and clustering of segments from clinical notes. Online. In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM). USA: IEEE, 2022, p. 1362-1368. ISBN 978-1-6654-6820-6. Available from: https://dx.doi.org/10.1109/BIBM55620.2022.9995229.

    2021

    1. SLANINÁKOVÁ, Terézia, Matej ANTOL, Jaroslav OĽHA and Vlastislav DOHNAL. Data-driven Learned Metric Index: an Unsupervised Approach. In 14th International Conference on Similarity Search and Applications (SISAP 2021). Cham: Springer, 2021, p. 81-94. ISBN 978-3-030-89656-0. Available from: https://dx.doi.org/10.1007/978-3-030-89657-7_7.
    2. NOVOTNÝ, Vít, Michal ŠTEFÁNIK, Dávid LUPTÁK, Martin GELETKA, Petr ZELINA and Petr SOJKA. Ensembling Math Information Retrieval Systems: MIRMU and MSM at ARQMath 2021. Online. In CEUR Workshop Proceedings, Volume 2936: 2021 Working Notes of CLEF - Conference and Labs of the Evaluation Forum, CLEF-WN 2021. Bucharest, Romania: CEUR-WS, 2021, p. 82-106. ISSN 1613-0073.
    3. MOHAMED, Sameh K., Brian WALSH, Mohan TIMILSINA, Maria TORRENTE, Fabio FRANCO, Mariano PROVENCIO, Adrianna JANIK, Luca COSTABELLO, Pasquale MINERVINI, Pontus STENETORP and Vít NOVÁČEK. On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer. Online. In Adam B. Wilcox, Randi Foraker, Kensaku Kawamoto, Yves A. Lussier, Nadine McCleary. Proceedings of AMIA 2021 Annual Symposium. San Diego: AMIA, 2021, p. 853-862. ISSN 1942-597X.
    4. NOVOTNÝ, Vít, Eniafe Festus AYETIRAN, Dalibor BAČOVSKÝ, Dávid LUPTÁK, Michal ŠTEFÁNIK and Petr SOJKA. One Size Does Not Fit All: Finding the Optimal Subword Sizes for FastText Models across Languages. In Mitkov, Ruslan and Angelova, Galia. Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021). Varna, Bulgaria: INCOMA Ltd., 2021, p. 1068-1074. ISBN 978-954-452-072-4. Available from: https://dx.doi.org/10.26615/978-954-452-072-4_120.
    5. TORRENTE, M., F. FRANCO, V. CALVO, A. Collazo LORDUY, E. MENASALVAS, M. E. VIDAL, P. SOUSA, J. PIMENTAO, Vít NOVÁČEK, P. MINERVINI, D. FEY, L. COSTABELLO, M. POCS and M. PROVENCIO. P08. 01 Building Personalized Follow-Up Care Through AI by Bringing the Lung Cancer Patient, Data Scientist and Oncologist Together. Journal of Thoracic Oncology. Elsevier, 2021, vol. 16, No 10, p. 991-992. ISSN 1556-1380. Available from: https://dx.doi.org/10.1016/j.jtho.2021.08.294.

    2020

    1. NOVOTNÝ, Vít and Marie STARÁ. Cthulhu Hails from Wales: N-gram Frequency Analysis of R'lyehian. In Aleš Horák, Pavel Rychlý, Adam Rambousek. Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020. Brno: Tribun EU, 2020, p. 87-92. ISBN 978-80-263-1600-8.
    2. MEDVEĎ, Marek, Radoslav SABOL and Aleš HORÁK. Efficient Management and Optimization of Very Large Machine Learning Dataset for Question Answering. In Aleš Horák. Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020. Brno: Tribun EU, 2020, p. 23-34. ISBN 978-80-263-1600-8.
    3. SUCHOMEL, Vít. Removing Spam from Web Corpora Through Supervised Learning and Semi-manual Classification of Web Sites. In Aleš Horák. Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020. Brno: Tribun 2020, 2020, p. 113-123. ISBN 978-80-263-1600-8.
    4. NOVOTNÝ, Vít. The Art of Reproducible Machine Learning: A Survey of Methodology in Word Vector Experiments. In Aleš Horák, Pavel Rychlý, Adam Rambousek. Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020. Brno: Tribun EU, 2020, p. 55-64. ISBN 978-80-263-1600-8.
    5. NOVOTNÝ, Vít, Petr SOJKA, Michal ŠTEFÁNIK and Dávid LUPTÁK. Three is Better than One: Ensembling Math Information Retrieval Systems. CEUR Workshop Proceedings. Thessaloniki, Greece: M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen., 2020, vol. 2020, No 2696, p. 93-122. ISSN 1613-0073.
    6. NOVOTNÝ, Vít, Michal ŠTEFÁNIK, Dávid LUPTÁK and Petr SOJKA. Towards Useful Word Embeddings: Evaluation on Information Retrieval, Text Classification, and Language Modeling. In Aleš Horák and Pavel Rychlý and Adam Rambousek. Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020. Brno: Tribun EU, 2020, p. 37-46. ISBN 978-80-263-1600-8.

    2019

    1. ŠIROKÝ, Filip. Anomaly Detection Using Deep Sparse Autoencoders for CERN Particle Detector Data. 2019.
    2. NOVOTNÝ, Vít. Soft Cosine Measure: Capturing Term Similarity in the Bag of Words VSM. 2019.

    2016

    1. BALÁŽIA, Michal and Petr SOJKA. Walker-Independent Features for Gait Recognition from Motion Capture Data. In Antonio Robles-Kelly, Marco Loog, Battista Biggio, Francisco Escolano, Richard Wilson. Proceedings of the joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2016) and Statistical Techniques in Pattern Recognition (SPR 2016). LNCS 10029. Switzerland: Springer International Publishing AG, 2016, p. 310-321. ISBN 978-3-319-49054-0. Available from: https://dx.doi.org/10.1007/978-3-319-49055-7_28.

    2009

    1. ŘEHŮŘEK, Radim and Milan KOLKUS. Language Identification on the Web: Extending the Dictionary Method. In Computational Linguistics and Intelligent Text Processing, 10th International Conference, CICLing 2009, Proceedings. první. Mexico City, Mexico: Springer-Verlag, 2009, p. 357-368. ISBN 978-3-642-00381-3. Available from: https://dx.doi.org/10.1007/978-3-642-00382-0_29.

    2008

    1. ŘEHŮŘEK, Radim and Petr SOJKA. Automated Classification and Categorization of Mathematical Knowledge. In Intelligent Computer Mathematics: AISC/Calculemus/MKM LNAI 5144. první. Berlin, Heidelberg, New York: Springer-Verlag, 2008, p. 543-557. ISBN 978-3-540--85109-7.
    2. MATERNA, Jiří. Automatic Web Page Classification. Online. In Recent Advances in Slavonic Natural Language Processing. Brno: Faculty of Informatics, Masaryk University, 2008, 10 pp. ISBN 978-80-210-4741-9.
    3. KOTT, Petr and Lubomír POPELÍNSKÝ. Automatická klasifikace transformovaných vět (Classification of transformed sentences). In Sborník konference SCO 2008. Brno: PřF MU, 2008, 6 pp. ISBN 978-80-210-4613-9.
    4. BRIATKOVÁ, Mária, Zdeněk KEDAJ and Lubomír POPELÍNSKÝ. DŽEMUj - dobývání znalostí z odpovědníků IS MU (DŽEMUj - data mining in electronic tests in IS MU). In Sborník konference SCO 2008. Brno: PřF MU, 2008, 6 pp. ISBN 978-80-210-4613-9.
    5. SOJKA, Petr. From Minds to Pixels and Back. první. Brno: Masarykova univerzita, 2008, xvi+209. habilitation thesis.
    6. VODÁK, Daniel and Lubomír POPELÍNSKÝ. Jak mravenčí kolonie dobývají znalosti (How An Ant Colony Mines Data). In Sborník 7. ročníku konference Znalosti. Bratislava: STU, 2008, p. 291-302. ISBN 978-80-227-2827-0.

    2007

    1. POPELÍNSKÝ, Lubomír. Advanced learning techniques for NLP. In 8th summer school of the European Masters in Language and Speech. 2007.
    2. SOJKA, Petr and Radim ŘEHŮŘEK. Classification of Multilingual Mathematical Papers in DML-CZ. In Proceedings of First Workshop of Recent Advances in Slavonic Natural Language Processing RASLAN 2007. první. Brno: Masarykova univerzita, 2007, p. 89-96. ISBN 978-80-210-4471-5.
    3. GREGAR, Tomáš, Radka POSPÍŠILOVÁ and Pavel ČÍŽEK. E-learning a sémantika obrazových dat (E-learning and image data semantics). In Sborník čtvrtého ročníku konference o e-learningu --- SCO 2007. Brno: Masarykova univerzita, 2007, p. 239-244, 260 pp. ISBN 978-80-210-4296-4.
    4. POPELÍNSKÝ, Lubomír and Jiří MATERNA. Keyness and Relational Learning (Keyness ans Relational Learning). In International conference Keyness in Text. Siena: University of Siena, 2007, p. 61-63.
    5. POMIKÁLEK, Jan and Radim ŘEHŮŘEK. The Influence of Preprocessing Parameters on Text Categorization. International Journal of Applied Science, Engineering and Technology. 2007, 4/2007, No 1, p. 430-434. ISSN 1307-4318.
    6. HUDÍK, Tomáš. The PAH Source Identification Using Positive Matrix Factorization and Clustering Methods. In 6th International Symposium on Environmental Software Systems. Glueph: The International Federation for Information Processing WG 5.11, 2007, p. 63-71. ISBN 978-3-901882-22-7.
    7. GREGAR, Tomáš and Radka POSPÍŠILOVÁ. Zvýšení využitelnosti obrazových dat ve výuce pomocí získaných sémantických informací (Improving of graphic data usability in learning via acquired semantic information). In Sborník 27. konference o geometrii a počítačové grafice. České Budějovice: ČSGG, 2007, p. 67-72. ISBN 978-80-85763-41-6.

    2006

    1. HUDÍK, Tomáš. The Machine-Learning Methods in the Environmental Risk Assessment Spatial Modelling. In Proceedings of the 2nd international summer school on computational biology. Brno: Masaryk Univerzity, 2006, p. 52-57. ISBN 80-7355-070-9.
    2. GREGAR, Tomáš and Radka POSPÍŠILOVÁ. Tvorba a využití vizuálních ontologií v elektronické podpoře výuky (Visual ontology creation and its usage in e-learning). In DATAKON 2006, Sborník databázové konference. Masarykova univerzita. Brno: Masarykova univerzita, 2006, p. 169-178, 9 pp. ISBN 80-210-4102-1.
    3. HUDÍK, Tomáš. Using Machine Learning Methods in Environmental Risk Assessment -- Overview. In EMEC7 The Book of Abstracts. Brno: Brno University of Technology, Faculty of Chemistry, 2006, p. 78. ISBN 80-214-3320-5.

    2005

    1. SOJKA, Petr. Competing Patterns in Language Engineering and Computer Typesetting. první. Brno: Masarykova univerzita, 2005, 140 pp. PhD. dissertation.
    2. BLAŤÁK, Jan. First-order Frequent Patterns in Text Mining. In EPIA'05, 12th Portuguese Conference on Artificial Intelligence. 1st ed. Covilha, Portugal: Institute of Electrical and Electronics Engineers, Inc., 2005, p. 344-350. ISBN 0-7803-9365-1.
    3. POPELÍNSKÝ, Lubomír and Jan BLAŤÁK. Learning genic interactions without expert domain knowledge: Comparison of different ILP algorithms. In Proceedings of ICML05 workshop on Learning Language in Logic (LLL05). Bonn: Fraunhofer Institute, 2005, p. 21-30.
    4. LIDMAN, Petr, Zdenko STANÍČEK, Filip PROCHÁZKA, Eva BUDINSKÁ, Jiří JARKOVSKÝ and Ladislav DUŠEK. Projekt EMIL (Effective Microarray IntelLigence): přínos metod umělé inteligence pro analýzu microarrays (Project EMIL (Effective Microarray IntelLigence): benefits of artificial intelligence methods for microarray analysis). In Sborník abstraktů konference se zahraniční účastí. Analytická cytometrie III. Brno: Česká společnost pro analytickou cytologii, 2005, p. 107-108. ISBN 80-239-5155-6.
    5. LIDMAN, Petr, Zdenko STANÍČEK, Filip PROCHÁZKA, Jan MUŽÍK, Ladislav DUŠEK, Rostislav VYZULA and Pavel ANDRES. Projekt UIRON ("Universal information robot in oncology"): přínos metod umělé inteligence v biomedicíně a klinické praxi (Project UIRON ("Universal information robot in oncology"): benefits of artificial intelligence methods in biomedicine & clinical practice). In Vybrané otázky onkologie IX. Praha: Galén, 2005, p. 143-144. ISBN 80-7262-382-6.
    6. HROZA, Jiří. Protein Secondary Structure Prediction by Machine Learning Methods. In 1st International Summer School on Computational Biology. Brno, Czech Republic: Masaryk University, 2005, p. 38-43, 5 pp. ISBN 80-210-3907-8.
    7. LIDMAN, Petr, Zdenko STANÍČEK, Filip PROCHÁZKA, Ladislav DUŠEK, Jiří JARKOVSKÝ and Eva BUDINSKÁ. Rule-based systems: employing intelligent computer assistant in biomedicine & clinical practice. In Proceedings of 1st International Summer School on Computational Biology. Brno: Masarykova univerzita, 2005, p. 100-104. ISBN 80-210-3907-8.
    8. HUDÍK, Tomáš and Matej LEXA. Segmentation of texts and biological sequences into lexical and structural units using a machine-learning approach. In Proceedings of the 1st International Summer School on Computational Biology. Brno: L. Dušek, L., J. Hřebíček, L. Jarkovský, 2005, p. 50-56, 8 pp. ISBN 80-210-3907-8.
    9. HROZA, Jiří and Jan ŽIŽKA. Selecting Interesting Articles Using Their Similarity Based Only on Positive Examples. In Computational linguistics and Intelligent Text Processing. Germany: Springer-Verlag Berlin Heidelberg, 2005, p. 608-611. ISBN 3-540-24523-5.

    2004

    1. HROZA, Jiří, Jan ŽIŽKA and Aleš BOUREK. Filtering Very Similar Text Documents: A Case Study. In Computational linguistics and Intelligent Text Processing. Germany: Springer-Verlag Berlin Heidelberg, 2004, p. 511-520. ISBN 3-540-21006-7.
    2. MRÁKOVÁ, Eva, Lubomír POPELÍNSKÝ and Jan BLAŤÁK. Víceslovné výrazy a klasifikace českých textů (Multiword expressions and Czech document classification). In Znalosti 2004, sborník posterů. 1st ed. Ostrava: VŠB--Technická univerzita Ostrava, 2004, p. 53-56.

    2003

    1. POPELÍNSKÝ, Lubomír. Disambiguation of case siffixes in Basque. In Proceedings of TALN Workshop "Traitement automatique des langues minoritaires et des petites langues. Batz-sur-Mer: ATALA, 2003, p. 213-222.
    2. POPELÍNSKÝ, Lubomír. Induktivní logické programování (Induktive logic programming). In Sborník konference DATAKON 2003. Brno: Masarykova univerzita, 2003, p. 111-130. ISBN 80-210-3215-4.
    3. ŽIŽKA, Jan, Michal ŠRÉDL and Aleš BOUREK. Searching for Significant Word Associations in Text Documents Using Genetic Algorithms. In Computional Linguistics and Intelligent Text Processing. Berlin Heidelberg New York: Springer Verlag, 2003, p. 584-587. ISBN 3-540-00532-3.
    4. POPELÍNSKÝ, Lubomír. Strojové učení a přirozený jazyk (abtrakt tutoriálu) (Machine learning and natural language processing). In Sborník konference ZNALOSTI 2003. Ostrava: FEI VŠB-TU Ostrava, 2003, p. 18-19. ISBN 80-248-0229-5.

    2002

    1. KŘIVÁNKOVÁ, Ludmila, Michal OČKO, Lubomír POPELÍNSKÝ and Petr BOČEK. Fast choice of separation conditions for analyses by capillary zone electrophoresis usingan information system Xemic. Electrophoresis. Wiley-VCH Verlag GmbH, 2002, vol. 23, No 19, p. 3364-3371. ISSN 0173-0835.

    2001

    1. DOBROVOLNÝ, Petr, Lubomír POPELÍNSKÝ and Petr KUBA. Využitelnost algoritmů strojového učení pro klasifikaci multispektrálního družicového snímku (Usefulness of machine learning algorithms for multispectral image classification). In GIS Ostrava 2001. Sborník konference. Ostrava: VŠB - TUO, 2001. ISSN 1213-2454.
    2. POPELÍNSKÝ, Lubomír, Petr DOBROVOLNÝ and Petr KUBA. Využití metod strojového učení pro klasifikaci družicových snímků (Using machine learning methods for classification of satellite images). In Sborník konference Znalosti 2001. Praha: Vysoká škola ekonomická, Praha, 2001, p. 1-6.

    2000

    1. KUBAT, Miroslav and Jan ŽIŽKA. Learning Middlegame Patterns in Chess: A Case Study. In Proceedings of the 13th International Conference on Industrial & Engineering Applications of AI & Expert Systems. New Orleans, LA, U.S.A.: Springer Verlag, 2000, p. 426-433. LNCS.
    2. BOUREK, Aleš and Jan ŽIŽKA. Monitorování asistované reprodukce a reprodukční medicíny pomocí Internetu (Use of the Internet for monitoring trends in assisted reproduction and reproductive medicine). 2000th ed. Třebechovice: Medexart, 2000, 4 pp. Gynekolog. ISBN 1210-1133.
    3. BOUREK, Aleš, Jan ŽIŽKA, Pavel VENTRUBA and Luděk FREY. Monitorování asistované reprodukce a reprodukční medicíny pomocí Internetu. (The use of the Internet for monitoring trends in assisted reproduction and reproductive medicine.). Gynekolog. Třebechovice: Medexart, 2000, vol. 2, No 6, p. 220-223. ISSN 1210-1133.
    4. POPELÍNSKÝ, Lubomír, Tomáš PAVELEK and Tomáš PTÁČNÍK. On Disambiguation in Czech Corpora. Brno (CZE): FI MU, 2000, 012 pp.
    5. ŽIŽKA, Jan, Aleš BOUREK and Luděk FREY. TEA: A Text Analysis Tool for the Intelligent Text Document Filtering. In Text, Speech and Dialogue. Berlin, Heidelberg, New York: Springer Verlag, 2000, p. 151-156. LNCS 1902. ISBN 3-540-41042-2.

    1998

    1. ŽIŽKA, Jan and Aleš BOUREK. Learning and Classifying Medical Text Documents Using the Naive Baye's Algorithm. Brno: FI MUNI / Konvoj, Brno, 1998, 4 pp. International Workshop on Text, Speech and Dialog. ISBN 80-210-1899-2.
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