Naslov
Information gain of structured medical diagnostic tests: Integration of Bayesian networks and ontologies

Autori
Prcela, Marin ; Gamberger, Dragan ; Šmuc, Tomislav ; Bogunović, Nikola ;

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of International Conference on Biomedical Engineering Systems and Technologies / Fred, Ana ; Filipe, Joaquim ; Gamboa, Hugo ; - : Institute for Systems and Technologies of Information, Control and Communication, 2010, 235-240

ISBN
978-989-674-016-0

Skup
BIOSTEC International Joint Conference on Biomedical Engineering Systems and Technologies

Mjesto i datum
Valencia, Španjolska, 20.01.2010. - 23.01.2010

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Knowledge representation; Ontologies; Bayesian networks; Integration; Information gain; Decision support system; Expert system

Sažetak
Usage of Bayesian networks in medical decision support system is in general case twofold: (1) for obtaining probabilities of occurrence of medical events (i.e. possible diagnosis) and (2) for obtaining information gain of actions that can be taken (i.e. diagnostic tests). On the other hand, typical role of ontology is to provide a framework for definition of medical concepts, their structure and relations among them. In medical practice diagnostic tests are commonly comprised of number of measurements or sub-tests – a structure which is straightforwardly described by ontological language. In this paper we are analyzing the information gain of such structured medical diagnostic tests. The purpose of this analysis is to allow finding (1) which structured medical diagnostic test is at the given point the most informative one and (2) which elementary measurements within a given diagnostic test are the most informative ones. Furthermore, we are analyzing some computational issues which arise in the reasoning process.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA