Prediction of Incident Dementia Using Patient Temporal Health Status

Sunyang Fu, Omar A. Ibrahim, Yanshan Wang, Maria Vassilaki, Ronald C. Petersen, Michelle M Mielke, Jennifer St Sauver, Sunghwan Sohn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Dementia is one of the most prevalent health problems in the aging population. Despite the significant number of people affected, dementia diagnoses are often significantly delayed, missing opportunities to maximize life quality. Early identification of older adults at high risk for dementia may help to maximize current quality of life and to improve planning for future health needs in dementia patients. However, most existing risk prediction models predominantly use static variables, not considering temporal patterns of health status. This study used an attention-based time-aware model to predict incident dementia that incorporated longitudinal temporal health conditions. The predictive performance of the time-aware model was compared with three traditional models using static variables and demonstrated higher predictive power.

Original languageEnglish (US)
Title of host publicationMEDINFO 2021
Subtitle of host publicationOne World, One Health - Global Partnership for Digital Innovation - Proceedings of the 18th World Congress on Medical and Health Informatics
EditorsPaula Otero, Philip Scott, Susan Z. Martin, Elaine Huesing
PublisherIOS Press BV
Pages757-761
Number of pages5
ISBN (Electronic)9781643682648
DOIs
StatePublished - Jun 6 2022
Event18th World Congress on Medical and Health Informatics: One World, One Health - Global Partnership for Digital Innovation, MEDINFO 2021 - Virtual, Online
Duration: Oct 2 2021Oct 4 2021

Publication series

NameStudies in Health Technology and Informatics
Volume290
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

Conference18th World Congress on Medical and Health Informatics: One World, One Health - Global Partnership for Digital Innovation, MEDINFO 2021
CityVirtual, Online
Period10/2/2110/4/21

Keywords

  • deep learning
  • dementia
  • machine learning

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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