Name
Title | ||
|---|---|---|
Trace Ratio Linear Discriminant Analysis for Medical Diagnosis: A Case Study of Dementia. |
Abstract | ||
|---|---|---|
Dementia is one of the most common neurological disorders among the elderly. Identifying those who are of high risk suffering dementia is important to the administration of early treatment in order to slow down the progression of dementia symptoms. However, to achieve accurate classification, significant amount of subject feature information are involved. Hence identification of demented subjects can be transformed into a pattern recognition problem with high-dimensional nonlinear datasets. In this paper, we introduce trace ratio linear discriminant analysis (TR-LDA) for dementia diagnosis. An improved ITR algorithm (iITR) is developed to solve the TR-LDA problem. This novel method can be integrated with advanced missing value imputation method and utilized for the analysis of the nonlinear datasets in many real-world medical diagnosis problems. Finally, extensive simulations are conducted to show the effectiveness of the proposed method. The results demonstrate that our method can achieve higher accuracies for identifying the demented patients than other state-of-art algorithms. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/LSP.2013.2250281 | IEEE Signal Process. Lett. |
Keywords | Field | DocType |
high risk suffering dementia,medical disorders,diseases,pattern recognition,real-world medical diagnosis problems,treatment,neurophysiology,medical diagnosis,geriatrics,dimensionality reduction,dementia diagnosis,pattern classification,high-dimensional nonlinear datasets,neurological disorders,subject feature information,state-of-art algorithms,feature extraction,trace ratio linear discriminant analysis,advanced missing value imputation method,classification,dementia symptom progression,medical diagnostic computing,pattern recognition problem,elderly,patient diagnosis,biomedical research,bioinformatics | Dimensionality reduction,Pattern recognition,Feature extraction,Artificial intelligence,Linear discriminant analysis,Missing value imputation,Pattern recognition problem,Mathematics,Medical diagnosis,Dementia | Journal |
Volume | Issue | ISSN |
20 | 5 | 1070-9908 |
Citations | PageRank | References |
9 | 0.49 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingbo Zhao | 1 | 125 | 10.52 |
| Rosa H M Chan | 2 | 182 | 22.79 |
| Peng Tang | 3 | 80 | 11.47 |
| Tommy W. S. Chow | 4 | 1904 | 141.76 |
| Savio W H Wong | 5 | 11 | 0.93 |