Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia

Ana Luiza Dallora, Leandro Minku, Emilia Mendes, Mikael Rennemark, Peter Anderberg, Johan Sanmartin Berglund

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Dementia is a neurodegenerative disorder that affects the older adult population. To date, no cure or treatment to change its course is available. Since changes in the brains of affected individuals could be evidenced as early as 10 years before the onset of symptoms, prognosis research should consider this time frame. This study investigates a broad decision tree multifactorial approach for the prediction of dementia, considering 75 variables regarding demographic, social, lifestyle, medical history, biochemical tests, physical examination, psychological assessment and health instruments. Previous work on dementia prognoses with machine learning did not consider a broad range of factors in a large time frame. The proposed approach investigated predictive factors for dementia and possible prognostic subgroups. This study used data from the ongoing multipurpose Swedish National Study on Aging and Care, consisting of 726 subjects (91 presented dementia diagnosis in 10 years). The proposed approach achieved an AUC of 0.745 and Recall of 0.722 for the 10-year prognosis of dementia. Most of the variables selected by the tree are related to modifiable risk factors; physical strength was important across all ages. Also, there was a lack of variables related to health instruments routinely used for the dementia diagnosis.

Original languageEnglish
Article number6674
Pages (from-to)1-18
JournalInternational Journal of Environmental Research and Public Health
Volume17
Issue number18
DOIs
Publication statusPublished - 14 Sept 2020

Keywords

  • Cost sensitive learning
  • Decision tree
  • Dementia
  • Machine learning
  • Modifiable risk factors
  • Prognosis
  • Wrapper feature selection

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Health, Toxicology and Mutagenesis

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