F. Segovia, C. Bastin, E. Salmon, J. Górriz, J. Ramírez, C. Phillips
{"title":"Automatic Differentiation between Alzheimer's Disease and Mild Cognitive Impairment Combining PET Data and Psychological Scores","authors":"F. Segovia, C. Bastin, E. Salmon, J. Górriz, J. Ramírez, C. Phillips","doi":"10.1109/PRNI.2013.45","DOIUrl":null,"url":null,"abstract":"In recent years, several approaches to develop computer aided diagnosis systems for dementia have been proposed. The purpose of this work is to measure the advantages of using not only brain images as data source for those systems but also some psychological scores. To this aim, we compared the accuracy rates achieved by systems that use psychological scores beside the image data in the classification step and systems that use only the image data. The experiments show that the formers achieve higher accuracy rates regardless of the procedure carried out to analyze the image data.","PeriodicalId":144007,"journal":{"name":"2013 International Workshop on Pattern Recognition in Neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Workshop on Pattern Recognition in Neuroimaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRNI.2013.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In recent years, several approaches to develop computer aided diagnosis systems for dementia have been proposed. The purpose of this work is to measure the advantages of using not only brain images as data source for those systems but also some psychological scores. To this aim, we compared the accuracy rates achieved by systems that use psychological scores beside the image data in the classification step and systems that use only the image data. The experiments show that the formers achieve higher accuracy rates regardless of the procedure carried out to analyze the image data.