0484058 20240103215257.420180104235959.9 000418391500021 8 s. P cav_un_epca*0484057978-80-7464-932-5188-195OstravaUniversity of Ostrava2017NovákVilémInuiguchiMasahiroŠtěpničkaMartin Machine Learning Data Analysis Bayesian networks Imbalanced Data Acute Myocardial Infarction cav_un_auth*0355858 70 Salman I. SY cav_un_auth*0101228 Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory 30 Vomlel Jiří UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2017/MTR/vomlel-0484058.pdf cav_un_auth*0332303 GA16-12010S GA ČR CZ Our research reported in this paper is twofold. In the first part of the paper we use standard statistical methods to analyze medical records of patients suffering myocardial infarction from the third world Syria and a developed country - the Czech Republic. One of our goals is to find whether there are statistically significant differences between the two countries. In the second part of the paper we present an idea how to deal with incomplete and imbalanced data for tree-augmented naive Bayesian (TAN). All results presented in this paper are based on a real data about 603 patients from a hospital in the Czech Republic and about 184 patients from two hospitals in Syria. cav_un_auth*0355859 Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty /20./ 20170917 20170920 Pardubice CZ JD 20000 20200 20205 2018 2 PR RVO:67985556 http://hdl.handle.net/11104/0279537 S 3+4 Proceedings Paper Computer Science Artificial Intelligence|Mathematics Applied 3+4 Proceedings Paper Computer Science Artificial Intelligence|Mathematics Applied 3+4 Proceedings Paper Computer Science Artificial Intelligence|Mathematics Applied 2017 SCOPUS PUBMED 000418391500021 WOS cav_un_epca*0484057 Proceedings of the 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, CZECH-JAPAN SEMINAR 2017 University of Ostrava 2017 Ostrava 188 195 978-80-7464-932-5 340 Novák Vilém 340 Inuiguchi Masahiro 340 Štěpnička Martin