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Bibliografie

Conference Paper (international conference)

A machine learning method for incomplete and imbalanced medical data

Salman I., Vomlel Jiří

: Proceedings of the 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, CZECH-JAPAN SEMINAR 2017, p. 188-195 , Eds: Novák Vilém, Inuiguchi Masahiro, Štěpnička Martin

: Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty /20./, (Pardubice, CZ, 20170917)

: GA16-12010S, GA ČR

: Machine Learning, Data Analysis, Bayesian networks, Imbalanced Data, Acute Myocardial Infarction

: http://library.utia.cas.cz/separaty/2017/MTR/vomlel-0484058.pdf

(eng): Our research reported in this paper is twofold. In the first part of the paper we use\nstandard statistical methods to analyze medical records of patients suffering myocardial\ninfarction from the third world Syria and a developed country - the Czech Republic.\nOne of our goals is to find whether there are statistically significant differences between\nthe two countries. In the second part of the paper we present an idea how to deal with\nincomplete and imbalanced data for tree-augmented naive Bayesian (TAN). All results\npresented in this paper are based on a real data about 603 patients from a hospital in\nthe Czech Republic and about 184 patients from two hospitals in Syria.

: JD

: 20205