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dc.contributor.authorMazzocco, Thomasen_UK
dc.contributor.authorHussain, Amiren_UK
dc.description.abstractClinicians often experience difficulties in the diagnosis of dementia due to the intrinsic complexity of the process and lack of comprehensive diagnostic tools. Different models have been proposed to provide medical decision support in dementia diagnosis. The aim of this study is to improve on the performance of a recent application of Bayesian belief networks using an alternative approach based on logistic regression. A pool of 14 variables has been evaluated in a sample of 164 patients suspected of dementia. First, a logistic regression model for dementia prediction is developed using all variables included in the previous model; then, a second model is built using a stepwise logistic regression starting with all collected variables and selecting the pool of the relevant ones. A range of performance metrics have been used to evaluate the developed models. The new models have resulted in very good predictive power, demonstrating general performance improvement compared to a state-of-the-art prediction model. Interestingly, the approach based on statistical variables selection outperformed the model which used variables selected by domain experts in the previous study. Further collaborative studies are now required to determine the optimal approach and to overcome existing limitations imposed by the size of the considered sample.en_UK
dc.relationMazzocco T & Hussain A (2012) Novel logistic regression models to aid the diagnosis of dementia. Expert Systems with Applications, 39 (3), pp. 3356-3361.
dc.rightsThe publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author; you can only request a copy if you wish to use this work for your own research or private study.en_UK
dc.subjectVariables selectionen_UK
dc.subjectLogistic regressionen_UK
dc.subjectPrediction modelen_UK
dc.subjectDecision support systemen_UK
dc.subjectDementia Diagnosesen_UK
dc.subjectRegression analysis Mathematical modelsen_UK
dc.titleNovel logistic regression models to aid the diagnosis of dementiaen_UK
dc.typeJournal Articleen_UK
dc.rights.embargoreason[Novel logistic regression models.pdf] The publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work.en_UK
dc.citation.jtitleExpert Systems with Applicationsen_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.affiliationUniversity of Stirlingen_UK
dc.contributor.affiliationComputing Scienceen_UK
rioxxterms.typeJournal Article/Reviewen_UK
local.rioxx.authorMazzocco, Thomas|en_UK
local.rioxx.authorHussain, Amir|0000-0002-8080-082Xen_UK
local.rioxx.projectInternal Project|University of Stirling|
local.rioxx.filenameNovel logistic regression models.pdfen_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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