L
Leonard Leibovici
Researcher at Rabin Medical Center
Publications - 22
Citations - 242
Leonard Leibovici is an academic researcher from Rabin Medical Center. The author has contributed to research in topics: Decision support system & Drug resistance. The author has an hindex of 7, co-authored 22 publications receiving 230 citations. Previous affiliations of Leonard Leibovici include Tel Aviv University.
Papers
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Journal ArticleDOI
Duration of antibacterial treatment for uncomplicated urinary tract infection in women.
TL;DR: Three days of antibiotic therapy is similar to 5-10 days in achieving symptomatic cure during uncomplicated UTI treatment, while the longer treatment is more effective in obtaining bacteriological cure.
Journal ArticleDOI
Duration of Antibacterial Treatment for Uncomplicated Urinary Tract Infection in Women
TL;DR: Three days of antibiotic therapy is similar to 5-10 days in achieving symptomatic cure during uncomplicated UTI treatment, while the longer treatment is more effective in obtaining bacteriological cure.
Journal ArticleDOI
Performance of the TREAT decision support system in an environment with a low prevalence of resistant pathogens
Kristian Kofoed,Alina Zalounina,Ove Andersen,Gorm Lisby,Mical Paul,Mical Paul,Leonard Leibovici,Leonard Leibovici,Steen Andreassen +8 more
TL;DR: The results of the study suggest that TREAT can improve the appropriateness of antimicrobial therapy and reduce the cost of side effects in regions with a low prevalence of resistant pathogens, however, at the expense of increased use of antibiotics.
Book ChapterDOI
A Probabilistic Network for Fusion of Data and Knowledge in Clinical Microbiology
Steen Andreassen,Leonard Leibovici,Mical Paul,Anders Dencker Nielsen,Alina Zalounina,L. E. Kristensen,Karsten Falborg,Brian Kristensen,Uwe Frank,Henrik Carl Schønheyder +9 more
TL;DR: The Treat project uses a probabilistic network to combine clinical signs, symptoms and laboratory results, and the problem of obtaining probabilities for the network is discussed.
Journal ArticleDOI
A stochastic model of susceptibility to antibiotic therapy-The effects of cross-resistance and treatment history
TL;DR: 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 predict the susceptibility to future antibiotic treatments is proposed, thus providing a systematic basis for revision of antibiotic treatment.