Distinguishing Lewy Body Dementia from Alzheimer's Disease using Machine Learning on Heterogeneous Data: A Feasibility Study

Niamh Mc Combe, Alok Joshi, David Finn, Paula McClean, Gemma Roberts, John O'Brien, Alan Thomas, Joseph Kane, KongFatt Wong-Lin

Research output: Contribution to conferencePaper

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Abstract

Dementia with Lewy Bodies (DLB) is the second most common form of dementia, but diagnostic markers for DLB can be expensive and inaccessible, and many cases of DLB
are undiagnosed. This work applies machine learning techniques to determine the feasibility of distinguishing DLB from Alzheimer’s Disease (AD) using heterogeneous data features. The Repeated Incremental Pruning to Produce Error Reduction (RIPPER) algorithm was first applied using a Leave-One-Out Cross-Validation protocol to a dataset comprising DLB and AD cases. Then, interpretable association rule-based diagnostic classifiers were obtained for distinguishing DLB from AD. The various diagnostic classifiers generated by this process had high accuracy over the whole dataset (mean accuracy of 94%). The mean accuracy in classifying their out-of-sample case was 80.5%. Every classifier generated consisted of very simple structure, each using 1-2 classification rules and 1-3 data features. As a group, the classifiers were heterogeneous and used several different data features. In particular, some of the
classifiers used very simple and inexpensive diagnostic features, yet with high diagnostic accuracy. This work suggests that opportunities may exist for incorporating accessible diagnostic assessments while improving diagnostic rate for DLB.
Original languageEnglish
Number of pages5
DOIs
Publication statusPublished - 8 Sep 2022
EventThe 44th International Engineering in Medicine and Biology Conference (EMBC) - Glasgow, United Kingdom
Duration: 11 Jul 202215 Jul 2022

Conference

ConferenceThe 44th International Engineering in Medicine and Biology Conference (EMBC)
Country/TerritoryUnited Kingdom
CityGlasgow
Period11/07/2215/07/22

Keywords

  • Dementia
  • dementia with Lewy bodies
  • feature selection
  • machine learning
  • Alzheimer disease

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