Title :
Bayesian networks for antibiotics prescription
Author :
Beuscart, R. ; Froudure, V. ; Dunhamel, A. ; Beuscart, C.
Author_Institution :
CERIM, Univ. de Lille II, France
Abstract :
Deals with the use of a Bayesian network as a computer-aided decision system. We have constructed a belief network for antibiotic prescription assistance in the case of urinary infections. The clinical diagnosis must have been made before using the belief network and the expertise is devoted to improving the choice of antibiotics. We compare our results with those given by human experts specialized in antibiotherapy. It proves to be quite efficient: in 29 clinical cases, the concordance kappa coefficient is as high as 0.67. This system can help the non-expert physician with antibiotherapy in non-trivial cases
Keywords :
belief networks; decision support systems; diseases; medical expert systems; patient treatment; Bayesian networks; antibiotherapy; antibiotic choice; antibiotics prescription; belief network; clinical diagnosis; computer-aided decision system; concordance kappa coefficient; human experts; nonexpert physician; urinary infections; Antibiotics; Bayesian methods; Clinical diagnosis; Computer networks; Costs; Humans; In vitro; Medical diagnostic imaging; Medical expert systems; Testing;
Conference_Titel :
[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-5674-8
DOI :
10.1109/IEMBS.1999.804011