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Early Diagnosis of Alzheimer Disease Using Instance-Based Learning Techniques
Khan, Aunsia1; Liu, Lian-Sheng2; Usman, Muhammad1; Fong, Simon3
2016-08-01
Source PublicationJournal of Medical Imaging and Health Informatics
ISSN2156-7018
Volume6Issue:4Pages:1111-1118
Abstract

Alzheimer's impairs thinking and memory ability while adversely affecting the quality of life. Machine learning and computer-aided diagnosis have gained increasing attention in the medical field especially for early Alzheimer's disease diagnosis. Several techniques achieved promising prediction accuracies, however they were evaluated on pathologically unproven data sets from diverse imaging modalities making it hard to make a rational comparison among them. Moreover, many other factors such as pre-processing, important attributes for feature selection, class imbalance, missing values in the data and the imaging quality, distinctively affect the assessment of the prediction accuracy. To overcome these limitations, our proposed model is based on data preprocessing and important features selection to eliminate the class imbalance and redundant attributes while retaining most relevant features. In particular, incremental classifiers were used instead of traditional batch learner, so to enable early diagnosis without waiting for the full training dataset to be available. Incremental classifiers are suitable for real-time diagnostic system. The comparison of classification accuracies suggest that the preprocessed data can yield higher prediction accuracies as compared to pathologically unproven raw data.

KeywordAlzheimer's Disease Computer Aided Diagnosis Machine Learning
DOIhttps://doi.org/10.1166/jmihi.2016.1808
URLView the original
Indexed BySCI
Language英语
WOS Research AreaMathematical & Computational Biology ; Radiology, Nuclear Medicine & Medical Imaging
WOS SubjectMathematical & Computational Biology ; Radiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000386493900030
PublisherAMER SCIENTIFIC PUBLISHERS, 26650 THE OLD RD, STE 208, VALENCIA, CA 91381-0751 USA
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Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.SZABIST, Dept Comp, Islamabad 44000, Pakistan
2.Guangzhou Univ TCM, Affiliated Hosp 1, Guangzhou 510405, Guangdong, Peoples R China
3.Univ Maccau, Dept Comp & Informat Sci, Maccau 999078, Peoples R China
Recommended Citation
GB/T 7714
Khan, Aunsia,Liu, Lian-Sheng,Usman, Muhammad,et al. Early Diagnosis of Alzheimer Disease Using Instance-Based Learning Techniques[J]. Journal of Medical Imaging and Health Informatics,2016,6(4):1111-1118.
APA Khan, Aunsia,Liu, Lian-Sheng,Usman, Muhammad,&Fong, Simon.(2016).Early Diagnosis of Alzheimer Disease Using Instance-Based Learning Techniques.Journal of Medical Imaging and Health Informatics,6(4),1111-1118.
MLA Khan, Aunsia,et al."Early Diagnosis of Alzheimer Disease Using Instance-Based Learning Techniques".Journal of Medical Imaging and Health Informatics 6.4(2016):1111-1118.
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