Physical Sciences and Mathematics Commons^™

Estimates Of Probable Dementia Prevalence From Population-Based Surveys Compared With Dementia Prevalence Estimates Based On Meta-Analyses, Kaarin J. Anstey, Richard A. Burns, Carole Birrell, David G. Steel, Kim M. Kiely, Mary A. Luszcz

Faculty of Informatics - Papers (Archive)

Background: National data on dementia prevalence are not always available, yet it may be possible to obtain estimates from large surveys that include dementia screening instruments. In Australia, many of the dementia prevalence estimates are based on European data collected between 15 and 50 years ago. We derived populationbased estimates of probable dementia and possible cognitive impairment in Australian studies using the Mini-Mental State Examination (MMSE), and compared these to estimates of dementia prevalence from meta-analyses of European studies.

Methods: Data sources included a pooled dataset of Australian longitudinal studies (DYNOPTA), and two Australian Bureau of Statistics National …

Investigation Of Relative Risk Estimates From Studies Of The Same Population With Contrasting Response Rates And Designs, Nicole M. Mealing, Emily Banks, Louisa R. Jorm, David G. Steel, Mark S. Clements, Kris D. Rogers

Faculty of Informatics - Papers (Archive)

Background: There is little empirical evidence regarding the generalisability of relative risk estimates from studies which have relatively low response rates or are of limited representativeness. The aim of this study was to investigate variation in exposure-outcome relationships in studies of the same population with different response rates and designs by comparing estimates from the 45 and Up Study, a population-based cohort study (self-administered postal questionnaire, response rate 18%), and the New South Wales Population Health Survey (PHS) (computer-assisted telephone interview, response rate ~60%).

Methods: Logistic regression analysis of questionnaire data from 45 and Up Study participants (n …

Business Rules Discovery From Process Design Repositories, Jantima Polpinij, Aditya K. Ghose, Hoa Khanh Dam

Faculty of Informatics - Papers (Archive)

Traditional process mining approaches focus on extracting process constraints or business rules from repositories of process instances. In this context, process designs or process models tend to be overlooked although they contain information that are valuable for the process of discovering business rules. This paper will propose an alternative approach to process mining in terms of using process designs as the mining resources. We propose a number of techniques for extracting business rules from repositories of business process designs or models, leveraging the well-known Apriori algorithm. Such business rules are then used as a prior knowledge for further analysing, verifying, …