SVIBOR - Papers quoted in CC - project code: 3-01-026
MINISTRY OF SCIENCE AND TECHNOLOGY
Strossmayerov trg 4, HR - 10000 ZAGREB
tel.: +385 1 459 44 44, fax: +385 1 459 44 69
E-mail: ured@znanost.hr
SVIBOR - Collecting Data on Projects in Croatia
Papers quoted in Current Contents on project 3-01-026
Quoted papers: 2
Other papers: 32
Total: 34
Title: A Microcopmuter Method for Continuous System Simulation in
Health Care
- Authors:
- Božikov, Jadranka (81645)
- Deželić, Đuro (9623)
Journal: Computer Methods and Programs in Biomedicine
Number: 1
ISSN: 0169-2607
Volume: 34
Year: 1991
Pages: from 17 to 25
Number of references: 8
Language: engleski
Summary: A method for continuous system simulation based on the use
ofstandard spreadsheet programs is developed and described. Itincludes
features such as model implementation, changes ofsimulation parameters,
execution of simulation experiments andtabular and graphic presentation of
simulation results. Themethod is used for simulation of infectious disease
(shigelosis)dynamics in population. The method is applicable for
continuoussimulation of deterministic systems.
Keywords: Simulation modeling, System dynamics, Infectious diseases modeling, Spreadsheet
Title: An Inductive Learning Method Versus the Common Statistical
Approach to Outcome Forecasting
- Authors:
- Kern, Josipa (20746)
- Težak-Benčić, Marija (49451)
- Vuletić, Silvije (54002)
- Deželić, Đuro (9623)
- Kujundžić, Mirjana (179003)
Journal: Collegium Antropologicum
Number: 2
ISSN: 0350-6134
Volume: 15
Year: 1991
Pages: from 283 to 289
Number of references: 11
Language: engleski
Summary: Decision tree construction through inductive learning
method andstatistical techniques, discriminant analysis and
Bayesianapproach, are compared. The problem example, gestationalage had to
be forecasted on the basis of variables describing thecurrent and previous
pregnancies. The highest prognostic accuracy(61.3% absolute, 53.1%
relative), was achieved by using "Firsttree than Bayes" approach.
Keywords: Inductive learning method, Forecasting
Information: svibor@znanost.hr
