Mild cognitive impairment diagnostic method based on SVM

Shi Pin Lv, Xiu Kun Wang, Yi Yuan Tang, Yan Sun, Yan Wang, Li Zhou

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

Mild Cognitive Impairment (MCI), the transitional stage from normal aging to the Alzheimer Disease (AD), is now regarded as the early stage of AD, and the research on MCI is significant for the early diagnosis and therapy of AD. Generally cognition and memory function examination are performed in diagnosis of MCI. It is easy to diagnose subjects as normal or MCI when all test indexes are identical, but the final diagnosis needs to be made by doctors according to their experiences if there is any difference among indexes. In this paper, a classifier was trained based on support vector machine (SVM) using the data of the subjects with confirmed diagnosis, and then to predict the state of those undiagnosed. The experiment showed the highest prediction accuracy achieved 87.6% according to doctors' diagnoses, and the method can be used in computer-aided diagnosis of MCI.

Original languageEnglish
Pages (from-to)229-233
Number of pages5
JournalChinese Journal of Biomedical Engineering
Volume27
Issue number2
StatePublished - Apr 2008

Keywords

  • Alzheimer disease
  • Mild cognitive impairment
  • Support vector machines

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