Acute heart failure (AHF) is a common and severe condition with a poor prognosis. Its course is o... more Acute heart failure (AHF) is a common and severe condition with a poor prognosis. Its course is often complicated by worsening renal function (WRF), exacerbating the outcome. The population of AHF patients experiencing WRF is heterogenous, and some novel possibilities for its analysis have recently emerged. Clustering is a machine learning (ML) technique that divides the population into distinct subgroups based on the similarity of cases (patients). Given that, we decided to use clustering to find subgroups inside the AHF population that differ in terms of WRF occurrence. We evaluated data from the three hundred and twelve AHF patients hospitalized in our institution who had creatinine assessed four times during hospitalization. Eighty-six variables evaluated at admission were included in the analysis. The k-medoids algorithm was used for clustering, and the quality of the procedure was judged by the Davies–Bouldin index. Three clinically and prognostically different clusters were d...
Acute heart failure (AHF) is a life-threatening, heterogeneous disease requiring urgent diagnosis... more Acute heart failure (AHF) is a life-threatening, heterogeneous disease requiring urgent diagnosis and treatment. The clinical severity and medical procedures differ according to a complex interplay between the deterioration cause, underlying cardiac substrate, and comorbidities. This study aimed to analyze the natural phenotypic heterogeneity of the AHF population and evaluate the possibilities offered by clustering (unsupervised machine-learning technique) in a medical data assessment. We evaluated data from 381 AHF patients. Sixty-three clinical and biochemical features were assessed at the admission of the patients and were included in the analysis after the preprocessing. The K-medoids algorithm was implemented to create the clusters, and optimization, based on the Davies-Bouldin index, was used. The clustering was performed while blinded to the outcome. The outcome associations were evaluated using the Kaplan-Meier curves and Cox proportional-hazards regressions. The algorithm ...
A number of stochastic models for modeling time series data can be found in the literature. Among... more A number of stochastic models for modeling time series data can be found in the literature. Among them models based on Log-normal distribution are more traditional, while models using Johnson SB or Johnson SU distributions were introduced recently. We present basic properties of the above-mentioned distributions and discuss their usability to model economic data. Data concerning the wages of more than two million Czech employees collected for more than twenty years are used for the comparison.
The paper summarizes the conception, data preparation and result evaluation of the LDMC, which ha... more The paper summarizes the conception, data preparation and result evaluation of the LDMC, which has been organized in connection with the DMoLD'13 - Data Mining on Linked Data Workshop, Prague, September 23 (as part of the ECML/PKDD conference program).
Encyclopedia of Information Science and Technology, Third Edition
The article covers basic principles of data mining, i.e. basic tasks and application areas, knowl... more The article covers basic principles of data mining, i.e. basic tasks and application areas, knowledge dicovery life cycle according to the CRISP-DM methodology. It also gives basic information about text mining and web mining.
In this chapter the focus is on demonstrating how different reasoning algorithms can be applied i... more In this chapter the focus is on demonstrating how different reasoning algorithms can be applied in multimedia analysis. Extracting semantics from images and videos has proved to be a very difficult task. On the other hand, artificial intelligence has made significant progress, especially in the area of knowledge technologies. Knowledge representation and reasoning form a research area that has been chosen by many researchers to enable the interpretation of the content of an image scene or a video shot. The rich theoretical ...
Pozvanie do znalostnej spolocnosti. Kyberkultura a internet, antiutopicke vizie a kriticke poznam... more Pozvanie do znalostnej spolocnosti. Kyberkultura a internet, antiutopicke vizie a kriticke poznamky, funkcie umenia v znalostnej spolocnosti, media art - umenie pre znalostnu spolecnosť?
... 978-80-227-2827-0. FIIT STU Bratislava, Ústav informatiky a softvérového ininierstva, 2008. ... more ... 978-80-227-2827-0. FIIT STU Bratislava, Ústav informatiky a softvérového ininierstva, 2008. ... Goldmann, L., Samour, A., Cobet, A., Sikora, T., Praks, P.: K-Space at TREVid ... NIST TRECVid 2007 - Text REtrieval Conference TRECVid Workshop, Gaithersburg, MD, 5-6 November ...
On selecting a constituent part of MU the "Overview of publishing activities" page will... more On selecting a constituent part of MU the "Overview of publishing activities" page will be displayed with information relevant to the selected constituent part. The "Overview of publishing activities" page is not available for non-activated items. ... HORÁKOVÁ, Jana - KELEMEN, Jozef - BERKA, Petr - BUREŠ, Vladimír - HVORECKÝ, Jozef - MIKULECKÝ, Peter. Pozvanie do znalostnej spoločnosti. Vyd. 1. Bratislava : Iura Edition (Wolters Kluwer), 2007. 265 pp. Iura Edition. ISBN 978 -80 -8078 -149 -1. ... Pozvanie do znalostnej spoločnosti. Kyberkultúra a internet, ...
Abstract. It becomes a good habit to organize a data mining cup, a competition or a challenge at ... more Abstract. It becomes a good habit to organize a data mining cup, a competition or a challenge at machine learning or data mining conferences. The main idea of the Discovery Challenge organized at the European Conferences on Principles and Practice of Knowledge Discovery in Databases since 1999 was to encourage a col-laborative research effort rather than a competition between data miners. Different 330 P. Berka, J. Rauch, M. Tomečková data sets have been used for the Discovery Challenge workshops during the seven years. The paper summarizes our experience gained when organizing and evaluating the Discovery Challenge on the atherosclerosis risk factor data.
Information about the category (type) of a WWW page can be helpful for the user within search, fi... more Information about the category (type) of a WWW page can be helpful for the user within search, filtering, as well as navigation tasks. We propose a multidimensional categorisation scheme, with bibliographic dimension as the primary one. We examine the possibilities and limits of performing such categorisation based on information extracted from URL, which is particularly useful for certain on-line applications such as meta-search or navigation support. In addition, we describe the problem of ambiguity of URL terms, and suggest a method for its partial overcoming by means of machine learning. As a side--effect, we show that general purpose WWW search engines can be used for providing input data for both human and computational analysis of the web. 1 Introduction The task of document categorisation is common within web applications, in particular for navigational, search and filtering systems, which give access to large amounts of documents. The aim of the categorisation may be . to e...
In this paper, we propose the application of rulebased reasoning for knowledge assisted image seg... more In this paper, we propose the application of rulebased reasoning for knowledge assisted image segmentation and object detection. A region merging approach is proposed based on fuzzy labeling and not on visual descriptors, while reasoning is used in evaluation of dissimilarity between adjacent regions according to rules applied on local information.
The paper describes some practical aspects of using LISp-Miner for data mining. LISp-Miner is a s... more The paper describes some practical aspects of using LISp-Miner for data mining. LISp-Miner is a software tool that is under development at the University of Economics, Prague. We will review the different types of knowledge patterns discovered by the system, and discuss their applicability for various data mining tasks. We also compare LISp-Miner 18.16 with Weka 3.6.9 and Rapid Miner 5.3.
Acute heart failure (AHF) is a common and severe condition with a poor prognosis. Its course is o... more Acute heart failure (AHF) is a common and severe condition with a poor prognosis. Its course is often complicated by worsening renal function (WRF), exacerbating the outcome. The population of AHF patients experiencing WRF is heterogenous, and some novel possibilities for its analysis have recently emerged. Clustering is a machine learning (ML) technique that divides the population into distinct subgroups based on the similarity of cases (patients). Given that, we decided to use clustering to find subgroups inside the AHF population that differ in terms of WRF occurrence. We evaluated data from the three hundred and twelve AHF patients hospitalized in our institution who had creatinine assessed four times during hospitalization. Eighty-six variables evaluated at admission were included in the analysis. The k-medoids algorithm was used for clustering, and the quality of the procedure was judged by the Davies–Bouldin index. Three clinically and prognostically different clusters were d...
Acute heart failure (AHF) is a life-threatening, heterogeneous disease requiring urgent diagnosis... more Acute heart failure (AHF) is a life-threatening, heterogeneous disease requiring urgent diagnosis and treatment. The clinical severity and medical procedures differ according to a complex interplay between the deterioration cause, underlying cardiac substrate, and comorbidities. This study aimed to analyze the natural phenotypic heterogeneity of the AHF population and evaluate the possibilities offered by clustering (unsupervised machine-learning technique) in a medical data assessment. We evaluated data from 381 AHF patients. Sixty-three clinical and biochemical features were assessed at the admission of the patients and were included in the analysis after the preprocessing. The K-medoids algorithm was implemented to create the clusters, and optimization, based on the Davies-Bouldin index, was used. The clustering was performed while blinded to the outcome. The outcome associations were evaluated using the Kaplan-Meier curves and Cox proportional-hazards regressions. The algorithm ...
A number of stochastic models for modeling time series data can be found in the literature. Among... more A number of stochastic models for modeling time series data can be found in the literature. Among them models based on Log-normal distribution are more traditional, while models using Johnson SB or Johnson SU distributions were introduced recently. We present basic properties of the above-mentioned distributions and discuss their usability to model economic data. Data concerning the wages of more than two million Czech employees collected for more than twenty years are used for the comparison.
The paper summarizes the conception, data preparation and result evaluation of the LDMC, which ha... more The paper summarizes the conception, data preparation and result evaluation of the LDMC, which has been organized in connection with the DMoLD'13 - Data Mining on Linked Data Workshop, Prague, September 23 (as part of the ECML/PKDD conference program).
Encyclopedia of Information Science and Technology, Third Edition
The article covers basic principles of data mining, i.e. basic tasks and application areas, knowl... more The article covers basic principles of data mining, i.e. basic tasks and application areas, knowledge dicovery life cycle according to the CRISP-DM methodology. It also gives basic information about text mining and web mining.
In this chapter the focus is on demonstrating how different reasoning algorithms can be applied i... more In this chapter the focus is on demonstrating how different reasoning algorithms can be applied in multimedia analysis. Extracting semantics from images and videos has proved to be a very difficult task. On the other hand, artificial intelligence has made significant progress, especially in the area of knowledge technologies. Knowledge representation and reasoning form a research area that has been chosen by many researchers to enable the interpretation of the content of an image scene or a video shot. The rich theoretical ...
Pozvanie do znalostnej spolocnosti. Kyberkultura a internet, antiutopicke vizie a kriticke poznam... more Pozvanie do znalostnej spolocnosti. Kyberkultura a internet, antiutopicke vizie a kriticke poznamky, funkcie umenia v znalostnej spolocnosti, media art - umenie pre znalostnu spolecnosť?
... 978-80-227-2827-0. FIIT STU Bratislava, Ústav informatiky a softvérového ininierstva, 2008. ... more ... 978-80-227-2827-0. FIIT STU Bratislava, Ústav informatiky a softvérového ininierstva, 2008. ... Goldmann, L., Samour, A., Cobet, A., Sikora, T., Praks, P.: K-Space at TREVid ... NIST TRECVid 2007 - Text REtrieval Conference TRECVid Workshop, Gaithersburg, MD, 5-6 November ...
On selecting a constituent part of MU the "Overview of publishing activities" page will... more On selecting a constituent part of MU the "Overview of publishing activities" page will be displayed with information relevant to the selected constituent part. The "Overview of publishing activities" page is not available for non-activated items. ... HORÁKOVÁ, Jana - KELEMEN, Jozef - BERKA, Petr - BUREŠ, Vladimír - HVORECKÝ, Jozef - MIKULECKÝ, Peter. Pozvanie do znalostnej spoločnosti. Vyd. 1. Bratislava : Iura Edition (Wolters Kluwer), 2007. 265 pp. Iura Edition. ISBN 978 -80 -8078 -149 -1. ... Pozvanie do znalostnej spoločnosti. Kyberkultúra a internet, ...
Abstract. It becomes a good habit to organize a data mining cup, a competition or a challenge at ... more Abstract. It becomes a good habit to organize a data mining cup, a competition or a challenge at machine learning or data mining conferences. The main idea of the Discovery Challenge organized at the European Conferences on Principles and Practice of Knowledge Discovery in Databases since 1999 was to encourage a col-laborative research effort rather than a competition between data miners. Different 330 P. Berka, J. Rauch, M. Tomečková data sets have been used for the Discovery Challenge workshops during the seven years. The paper summarizes our experience gained when organizing and evaluating the Discovery Challenge on the atherosclerosis risk factor data.
Information about the category (type) of a WWW page can be helpful for the user within search, fi... more Information about the category (type) of a WWW page can be helpful for the user within search, filtering, as well as navigation tasks. We propose a multidimensional categorisation scheme, with bibliographic dimension as the primary one. We examine the possibilities and limits of performing such categorisation based on information extracted from URL, which is particularly useful for certain on-line applications such as meta-search or navigation support. In addition, we describe the problem of ambiguity of URL terms, and suggest a method for its partial overcoming by means of machine learning. As a side--effect, we show that general purpose WWW search engines can be used for providing input data for both human and computational analysis of the web. 1 Introduction The task of document categorisation is common within web applications, in particular for navigational, search and filtering systems, which give access to large amounts of documents. The aim of the categorisation may be . to e...
In this paper, we propose the application of rulebased reasoning for knowledge assisted image seg... more In this paper, we propose the application of rulebased reasoning for knowledge assisted image segmentation and object detection. A region merging approach is proposed based on fuzzy labeling and not on visual descriptors, while reasoning is used in evaluation of dissimilarity between adjacent regions according to rules applied on local information.
The paper describes some practical aspects of using LISp-Miner for data mining. LISp-Miner is a s... more The paper describes some practical aspects of using LISp-Miner for data mining. LISp-Miner is a software tool that is under development at the University of Economics, Prague. We will review the different types of knowledge patterns discovered by the system, and discuss their applicability for various data mining tasks. We also compare LISp-Miner 18.16 with Weka 3.6.9 and Rapid Miner 5.3.
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