Naslov
Noise elimination applied in early diagnosis of rheumatic diseases

Autori
Lavrač, Nada ; Gamberger, Dragan ; Džeroski, Sašo

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Intelligent Data Analysis in Medicine and Pharmacology

Urednik/ci
Lavrač, Nada ; Keravnou, Elpida ; Zupan, Blaž

Izdavač
Kluwer Academic Publishers

Grad
Boston : Dordrecht : London

Godina
1997

Raspon stranica
187-205

Ključne riječi
machine learning, noise detection, rheumatology

Sažetak
Machine learning methods can be used to induce diagnostic rules from patient records with known diagnoses. In a medical application it is crucial that a machine learning system is capable of detecting regularities in the data by appropriately dealing with imperfect data, i.e., data that contains various kinds of errors, either random or systematic. The paper presents a compression-based method that is capable of detecting data which is suspected to contain errors and is therefore unsuited for the extraction of regularities genuine to this dataset. This noise elimination method is applied to a problem of early diagnosis of rheumatic diseases which is known to be difficult due to its nature and to the imperfections in the available dataset. The method is evaluated by applying the noise elimination algorithm in conjunction with the CN2 rule induction algorithm, and by comparing their performance to earlier results obtained by CN2 in this diagnostic domain.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika

POVEZANOST RADA