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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F10%3A00168849%21RIV11-MSM-21230___
rdf:type
n14:Vysledek skos:Concept
dcterms:description
Myocardial infarction (MI) is one of the most common causes of death or disability. An early detection of MI greatly improves patient's chances of surviving and returning to health. In this work we focused on inferior MI detection; our database consisted of 6350 ECG records. Interpretation of records was made by cardiologist and 512 records were diagnosed as an inferior MI. Prediction of inferior MI was acquired by the Selvester QRS score, the Novacode, and the Siemens 440/740. Moreover, we compared performance of learning algorithms Ripper, C4.5, SVM, and Naive Bayes to the decision systems. The best decision system,the Selvester score, achieved 0.58 of sensitivity and 0.93 of specificity. The better results were obtained by Ripper - sensitivity 0.83, specificity 0.92. The modification of Selvester yielded to similar performance of 0.85 sensitivity and 0.90 specificity. Myocardial infarction (MI) is one of the most common causes of death or disability. An early detection of MI greatly improves patient's chances of surviving and returning to health. In this work we focused on inferior MI detection; our database consisted of 6350 ECG records. Interpretation of records was made by cardiologist and 512 records were diagnosed as an inferior MI. Prediction of inferior MI was acquired by the Selvester QRS score, the Novacode, and the Siemens 440/740. Moreover, we compared performance of learning algorithms Ripper, C4.5, SVM, and Naive Bayes to the decision systems. The best decision system,the Selvester score, achieved 0.58 of sensitivity and 0.93 of specificity. The better results were obtained by Ripper - sensitivity 0.83, specificity 0.92. The modification of Selvester yielded to similar performance of 0.85 sensitivity and 0.90 specificity.
dcterms:title
Using One-Rule Algorithm To Find Optimal Thresholds For Detection Of Inferior Myocardial Infarction Using One-Rule Algorithm To Find Optimal Thresholds For Detection Of Inferior Myocardial Infarction
skos:prefLabel
Using One-Rule Algorithm To Find Optimal Thresholds For Detection Of Inferior Myocardial Infarction Using One-Rule Algorithm To Find Optimal Thresholds For Detection Of Inferior Myocardial Infarction
skos:notation
RIV/68407700:21230/10:00168849!RIV11-MSM-21230___
n3:aktivita
n15:Z n15:S
n3:aktivity
S, Z(MSM6840770012)
n3:dodaniDat
n9:2011
n3:domaciTvurceVysledku
n7:8323178 n7:9431446 n7:9446516 n7:7470509
n3:druhVysledku
n8:D
n3:duvernostUdaju
n18:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
294808
n3:idVysledku
RIV/68407700:21230/10:00168849
n3:jazykVysledku
n4:eng
n3:klicovaSlova
ECG; myocardial infarction; classification
n3:klicoveSlovo
n20:ECG n20:myocardial%20infarction n20:classification
n3:kontrolniKodProRIV
[9862AD8EC810]
n3:mistoKonaniAkce
Brno
n3:mistoVydani
Brno
n3:nazevZdroje
Analysis of Biomedical Signals and Images, BIOSIGNAL 2010, Proceedings
n3:obor
n16:JC
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
5
n3:rokUplatneniVysledku
n9:2010
n3:tvurceVysledku
Spilka, Jiří Lhotská, Lenka Chudáček, Václav Hanuliak, M. Kužílek, Jakub
n3:typAkce
n10:EUR
n3:zahajeniAkce
2010-06-27+02:00
n3:zamer
n19:MSM6840770012
s:issn
1211-412X
s:numberOfPages
7
n12:hasPublisher
Vysoké učení technické v Brně
n21:isbn
978-80-214-4106-4
n5:organizacniJednotka
21230