TY - GEN
T1 - Transferability modelling in the TREAT decision support system
AU - Zalounina, Alina
AU - Andreassen, Steen
AU - Leibovici, Leonard
AU - Paul, Mical
N1 - Funding Information:
This work was supported by a grant from NAABIIT programme (2106-05-0026) and a grant from the European Commission for the TREAT-project under the IST programme (IST-1999-1145).
PY - 2008
Y1 - 2008
N2 - One of the key-components for success of a decision support system is in its flexibility and applicability to different clinical locations. The present study is devoted to a system which is capable of successful transfer to a distant environment. We have developed a decision support system for antibiotic treatment (TREAT), which was adapted to four different hospitals in Europe. The system is based on a causal probabilistic network (CPN). The purpose of this paper is to present the models for transferability used in TREAT. The problem of transferability is addressed in the context of CPNs, emphasising the advantages of use of CPNs for solving the problem. The process of adapting TREAT is relatively easy; that is due to the modularity of the system. The system has been built using a modular architecture that allows rapid transfer of the system to different clinical environments. Such modularity can be archived by simple means which include the universal and modular structure of the CPN, the establishment of a large group of conditional probabilities in the CPN that are assumed to be independent of time and place, and the use of hierarchical Dirichlet methods for learning of data. Due to the universal structure of the CPN, the problem of transferability in TREAT concerns only the medical domain factors, not the topology of the system.
AB - One of the key-components for success of a decision support system is in its flexibility and applicability to different clinical locations. The present study is devoted to a system which is capable of successful transfer to a distant environment. We have developed a decision support system for antibiotic treatment (TREAT), which was adapted to four different hospitals in Europe. The system is based on a causal probabilistic network (CPN). The purpose of this paper is to present the models for transferability used in TREAT. The problem of transferability is addressed in the context of CPNs, emphasising the advantages of use of CPNs for solving the problem. The process of adapting TREAT is relatively easy; that is due to the modularity of the system. The system has been built using a modular architecture that allows rapid transfer of the system to different clinical environments. Such modularity can be archived by simple means which include the universal and modular structure of the CPN, the establishment of a large group of conditional probabilities in the CPN that are assumed to be independent of time and place, and the use of hierarchical Dirichlet methods for learning of data. Due to the universal structure of the CPN, the problem of transferability in TREAT concerns only the medical domain factors, not the topology of the system.
KW - Biomedical system modeling, simulation and visualization
KW - Decision support and control
UR - http://www.scopus.com/inward/record.url?scp=79961018597&partnerID=8YFLogxK
U2 - 10.3182/20080706-5-KR-1001.2206
DO - 10.3182/20080706-5-KR-1001.2206
M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???
AN - SCOPUS:79961018597
SN - 9783902661005
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
BT - Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
T2 - 17th World Congress, International Federation of Automatic Control, IFAC
Y2 - 6 July 2008 through 11 July 2008
ER -