Parkinson's disease subtype classification: Application of decision tree, logistic regression and logit leaf model

A. Nurrohman, S. Abdullah, H. Murfi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Parkinson's Disease has two subtypes which are Tremor Dominant (TD) and Postural Instability/Gait Difficulty (PIGD). Each subtype has the difference in clinical treatment, so it is necessary to classify Parkinson's Disease subtypes. Three classification methods were implemented: decision tree, logistic regression, and logit leaf model (LLM). Data on 229 people with early Parkinson's disease from the PPMI (Parkinson's Progression Markers Initiative) database were used in the analysis. Imbalanced data problem were handled using oversampling, undersampling, SMOTE (Synthetic Minority Over-sampling Technique). Logistic regression with SMOTE using parameter set-up α=600, γ=200 produced the best result, according to the accuracy of 98.3 %, sensitivity of 98.41 %, and specificity of 99.07 %.

Original languageEnglish
Title of host publicationProceedings of the 5th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2019
EditorsTerry Mart, Djoko Triyono, Tribidasari Anggraningrum Ivandini
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735420014
DOIs
Publication statusPublished - 1 Jun 2020
Event5th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2019 - Depok, Indonesia
Duration: 9 Jul 201910 Jul 2019

Publication series

NameAIP Conference Proceedings
Volume2242
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference5th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2019
Country/TerritoryIndonesia
CityDepok
Period9/07/1910/07/19

Keywords

  • Decision tree
  • logistic regression
  • logit leaf model (LLM)
  • Parkinson's disease
  • postural instability/gait difficulty (PIGD)
  • tremor dominant (TD)

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