Development of a Two-State Gaussian Hidden Markov Model for Modelling Dementia Progression in Patients with Mild Cognitive Impairment

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

Abstract

Dementia is characterized by a progressive deterioration of brain function affecting mental processes, such as memory, problem-solving, and concentration. Modelling of dementia progression can provide important insights into the disease process through the visualization and evaluation of disease trajectories. To demonstrate dynamic changes that can take place during the course of a disease trajectory in patients with mild cognitive impairment (MCI), we propose a Gaussian Hidden Markov Model (HMM) that incorporates non-invasive markers commonly used for assessing cognitive and functional changes in dementia diagnostics. We train our model in an unsupervised manner using the Baum-Welch Expectation-Maximization method and evaluate its performance by comparing HMM states with the corresponding ground-truth labels, not used during the model development phase. We believe our HMM framework can contribute to a better understanding of conversion to dementia and be used to support clinical decisions in real world situations.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 9th International Conference on Healthcare Informatics (ICHI)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages113-119
Number of pages7
ISBN (Electronic)9781665401326
ISBN (Print)978-1-6654-2980-1
DOIs
Publication statusPublished - 15 Oct 2021
Event9th IEEE International Conference on Healthcare Informatics, ICHI 2021 - Virtual, Victoria, Canada
Duration: 9 Aug 202112 Aug 2021

Conference

Conference9th IEEE International Conference on Healthcare Informatics, ICHI 2021
Abbreviated titleICHI 2021
Country/TerritoryCanada
CityVirtual, Victoria
Period9/08/2112/08/21

Keywords

  • Cognitive assessment
  • Cognitive decline
  • Cognitive impairment
  • Dementia
  • Dementia care
  • Early detection
  • Hidden markov model
  • Machine learning
  • Mild cognitive impairment
  • Neuropsychological test
  • Prediction
  • Predictive model
  • Probabilistic model
  • Unsupervised

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