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

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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 Organisation 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: Recent Applications and Developments
EditorsJenny Carter, Tianhua Chen, Francisco Chiclana Parilla, Arjab Singh Khuman
PublisherSpringer Nature
Publication statusAccepted/In press - 15 Oct 2020


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