Pregled bibliografske jedinice broj: 303157
Contrast Set Mining for Distinguishing between Similar Diseases
Contrast Set Mining for Distinguishing between Similar Diseases // Artificial Intelligence in Medicine / Belazzi, Ricarrdo ; Abu-Hanna, Ameen ; Hunter, Jim (ur.).
Berlin : Heidelberg: Springer, 2007. str. 109-118 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 303157 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Contrast Set Mining for Distinguishing between Similar Diseases
Autori
Kralj, Petra ; Lavrač, Nada ; Gamberger, Dragan ; Krstačić, Antonija
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Artificial Intelligence in Medicine
/ Belazzi, Ricarrdo ; Abu-Hanna, Ameen ; Hunter, Jim - Berlin : Heidelberg : Springer, 2007, 109-118
ISBN
978-3-540-73598-4
Skup
11th Conference on Artificial Intelligence in Medicine, AIME 2007
Mjesto i datum
Amsterdam, Nizozemska, 07.07.2007. - 11.07.2007
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
subgroup discovery; rule learning; contrast set mining
Sažetak
The task addressed and the method proposed in this paper aim at improved understanding of differences between similar diseases. In particular we address the problem of distinguishing between thrombolic brain stroke and embolic brain stroke as an application of our approach of contrast set mining through subgroup discovery. We describe methodological lessons learned in the analysis of brain ischaemia data and a practical implementation of the approach within an open source data mining toolbox.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
098-0982560-2563 - Algoritmi strojnog učenja i njihova primjena (Gamberger, Dragan, MZOS ) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb,
Klinika za traumatologiju
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus
