@misc{Misztal_Małgorzata_Wykorzystanie_2006,
 author={Misztal, Małgorzata},
 year={2006},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 description={Prace Naukowe Akademii Ekonomicznej we Wrocławiu. Taksonomia (13); 2006; nr 1126, s. 456-464},
 publisher={Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu},
 language={pol},
 abstract={The objective of the paper was to evaluate mortality and morbidity risk in patients undergoing coronary artery bypass grafting (CABG) and to define some decision rules assigning patients to selected risk subgroups. All the rules were establish on the basis of tree-structured algorithms: LOTUS and PLUS. Both of them are designed to fit a piecewise (multiple or simple) linear logistic regression model by recursively partitioning the data and fitting a different logistic regression in each partition. All the analyses were performed on the dataset of 3770 patients treated surgically due to coronary artery disease during October 2003 to December 2004 in 12 Polish Cardiac Departments.},
 type={artykuł},
 title={Wykorzystanie drzew regresji logistycznej do prognozowania ryzyka zgonu i powikłań pooperacyjnych u pacjentów z chorobą wieńcową},
}