Logit and fuzzy models analysis: estimation of risk in cardiac patients.
| Authors | |
|---|---|
| Year of publication | 2010 |
| Type | Article in Periodical |
| Magazine / Source | Physiological Research |
| MU Faculty or unit | |
| Citation | |
| Field | Physiology |
| Keywords | Risk prediction; myocardial infarction; implantable cardioverter-defibrillator; fuzzy logic; area under receiver operating characteristic; logistic regression |
| Description | 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. |
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