A Predictive Model for Identifying Possible MCI to AD Conversions in the ADNI Database

Author

Qu, Xiuyun ; Yuan, Bo ; Liu, Wenhuang

Author_Institution

Grad. Sch. at Shenzhen, Tsinghua Univ., Shenzhen, China

Volume

3

fYear

2009

fDate

Nov. 30 2009-Dec. 1 2009

Firstpage

102

Lastpage

105

Abstract

Alzheimer´s disease (AD) is one of the most common forms of dementia and has become a serious issue among the elderly in the aging society. Since AD is incurable and degenerative, early diagnosis is essential, which can give patients and their family more opportunities to arrange their lives. In the meantime, histopathologic studies have found that MCI (mild cognitive impairment) subjects usually have intermediate levels of AD pathology. In this paper, a predictive model is developed for identifying possible conversions from MCI to AD based on the ADNI (Alzheimer´s disease neuroimaging initiative) database. It is shown that, with the help of a range of advanced data mining techniques, the developed model can achieve promising performance with AUC around 0.88.

Keywords

data mining; database management systems; medical computing; Alzheimer disease conversion; Alzheimer disease neuroimaging initiative database; data data mining techniques; mild cognitive impairment; Aging; Alzheimer´s disease; Biomarkers; Databases; Dementia; Face detection; Machine learning; Neuroimaging; Predictive models; Senior citizens; ADNI; Alzheimer´s Disease; feature selection; imbalanced data;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3888-4

Type

conf

DOI

10.1109/KAM.2009.36

Filename

5362430