Alina Zalounina

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OBJECTIVE Selection of antibiotic therapy is a complicated process, depending on, among others, the effect of cross-resistance between antibiotics. We propose a model, which incorporates information about treatment history in the form of information on the success or failure of the current treatment and which combines this with data on cross-resistance to(More)
Estimation of probabilities by classical maximum likelihood estimators can give unreliable results when the number of cases is small. A Bayesian approach, where a priori probabilities with Dirichlet distributions are used to temper the estimates, can reduce the variance enough to make the estimates useful. This is demonstrated by using this approach to(More)
OBJECTIVES This paper describes the methods used in the International Cancer Benchmarking Partnership Module 4 Survey (ICBPM4) which examines time intervals and routes to cancer diagnosis in 10 jurisdictions. We present the study design with defining and measuring time intervals, identifying patients with cancer, questionnaire development, data management(More)
BACKGROUND An antibiogram (ABG) gives the results of in vitro susceptibility tests performed on a pathogen isolated from a culture of a sample taken from blood or other tissues. The institutional cross-ABG consists of the conditional probability of susceptibility for pairs of antimicrobials. This paper explores how interpretative reading of the isolate ABG(More)
The decision support system TREAT advices on antibiotic treatment of severe infections. A multicenter randomized clinical trial has demonstrated that Treat reduces inappropriate treatment by 50%. This paper will show that TREAT satisfies several features closely correlated with decision support sys-tems's ability to improve clinical practice. Examples of(More)
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