Affiliations 

  • 1 School of Accounting and Finance, Faculty of Business and Law, Taylor's University, Subang Jaya, Selangor, Malaysia
  • 2 Department of Mathematical and Actuarial Sciences, Universiti Tunku Abdul Rahman, Selangor, Malaysia
  • 3 Department of Neurology, Show Chwan Memorial Hospital, Changhua
  • 4 Department of Applied Mathematics, Tunghai University, Taichung
Am J Alzheimers Dis Other Demen, 2020;35:1533317520970788.
PMID: 33176431 DOI: 10.1177/1533317520970788

Abstract

BACKGROUND/AIMS: This study used HAICDDS screening questionnaire to classify the severity of dementia in Taiwan based on the clinical dementia rating scale.

METHODS: LDA was applied to 6,328 Taiwanese clinical patients for classification purposes. Clustering method was used to identify the associated influential symptoms for each severity level.

RESULT: LDA shows only 36 HAICDDS questions are significant to distinguish the 5 severity levels with 80% overall accuracy and it increased to 85.83% when combining normal and MCI groups. Severe dementia patients have the most serious declination in most cognitive and functionality domains, follows by moderate dementia, mild dementia, MCI and normal patients.

CONCLUSION: HAICDDS is a reliable and time-saved diagnosis tool in classifying the severity of dementia before undergoing a more in-depth clinical examination. The modified CDR may be indicated for epidemiological study and provide a solid foundation to develop a machine-learning derived screening instrument to detect dementia symptoms.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.