Detailed Information on Publication Record
2010
Logit and fuzzy models analysis: estimation of risk in cardiac patients.
HONZÍK, Petr, Lubomír KŘIVAN, Petr LOKAJ, Růžena LÁBROVÁ, Zuzana NOVÁKOVÁ et. al.Basic information
Original name
Logit and fuzzy models analysis: estimation of risk in cardiac patients.
Name in Czech
Logitová a fuzzy analýza: stanovení rizikovosti pacientů s chorobami srdce.
Authors
HONZÍK, Petr (203 Czech Republic), Lubomír KŘIVAN (203 Czech Republic), Petr LOKAJ (203 Czech Republic), Růžena LÁBROVÁ (203 Czech Republic), Zuzana NOVÁKOVÁ (203 Czech Republic), Bohumil FIŠER (203 Czech Republic) and Nataša HONZÍKOVÁ (203 Czech Republic, guarantor)
Edition
Physiological Research, Praha, Academy of Sciences of the Czech Rep. 2010, 0862-8408
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
30105 Physiology
Country of publisher
Czech Republic
Confidentiality degree
není předmětem státního či obchodního tajemství
Impact factor
Impact factor: 1.646
RIV identification code
RIV/00216224:14110/10:00044677
Organization unit
Faculty of Medicine
UT WoS
000279049100013
Keywords in English
Risk prediction; myocardial infarction; implantable cardioverter-defibrillator; fuzzy logic; area under receiver operating characteristic; logistic regression
Tags
International impact, Reviewed
Změněno: 6/10/2010 14:53, prof. MUDr. Nataša Honzíková, CSc.
Abstract
V originále
The individual risk factors and more complex approaches were used, which take into account that a borderline between a risky and non-risky value of each predictor is not clear-cut (fuzzification of a critical value) and that individual risk factors have different weight (area under receiver operating curve - AUC or Sommers D - Dxy). The risk factors were baroreflex sensitivity, ejection fraction and the number of ventricular premature complexes/hour on Holter monitoring. Those factors were evaluated separately and they were involved into logit model and fuzzy models (Fuzzy, Fuzzy-AUC, and Fuzzy-Dxy). The application of logit and fuzzy models was superior over the risk stratification based on algorithm where the decision making is dependent on one parameter.
Links
MSM0021622402, plan (intention) |
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