Diagnosing Alzheimer's disease using a self-organising fuzzy classifier

Jonathan Stirling, Tianhua Chen, Magda Bucholc

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)


Dementia is one of the major causes of disability and dependency among older people worldwide. Without treatment currently available to cure dementia or to alter its progressive course, one of the principal goals for dementia care set by the World Health Organization is the early diagnosis in order to promote early and optimal management. In recognition of the potentials of fuzzy systems in effectively dealing with medical data, this chapter investigates the use of a very recently proposed Self-Organising Fuzzy (SOF) classifier for the prediction of Alzheimer's Disease against Mild Cognitive Impairment and being Cognitively Unimpaired with patient observations provided by the renowned Alzheimer's Disease Neuroimaging Initiative repository. The experimental study demonstrates the effectiveness of SOF, especially in combined use with the Recursive Feature Elimination feature selection.

Original languageEnglish
Title of host publicationFuzzy Logic
Subtitle of host publicationRecent Applications and Developments
PublisherSpringer International Publishing
Number of pages14
ISBN (Electronic)9783030664749
ISBN (Print)9783030664732
Publication statusPublished (in print/issue) - 5 May 2021

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2021.


  • Alzheimer's disease
  • Clinical decision support
  • Dementia diagnosis
  • Fuzzy systems
  • Self-organising fuzzy classifier
  • SOF


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