@inproceedings{988531d177b14cacb9a2e682ab61b02e,
title = "Prediction of Incident Dementia Using Patient Temporal Health Status",
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.",
keywords = "deep learning, dementia, machine learning",
author = "Sunyang Fu and Ibrahim, {Omar A.} and Yanshan Wang and Maria Vassilaki and Petersen, {Ronald C.} and Mielke, {Michelle M.} and {St Sauver}, Jennifer and Sunghwan Sohn",
note = "Funding Information: This study was supported by NIA R01 AG068007 and NIAID R21 AI142702. The Mayo Clinic Study of Aging was supported by National Institutes of Health (NIH) Grants U01 AG006786, P50 AG016574, R01AG057708, the GHR Foundation, the Mayo Foundation for Medical Education and Research and was made possible by the Rochester Epidemiology Project (R01 AG034676). Funding Information: Maria Vassilaki has received research funding from Roche and Biogen; she currently consults for Roche, receives research funding from NIH, and has equity ownership in Abbott Laboratories, Johnson and Johnson, Medtronic, and Amgen. Jennifer St. Sauver has received research funding from Exact Sciences to study colorectal cancer. Michelle M. Mielke has consulted for Biogen and Brain Protection Company and receives research funding from NIH and DOD. Publisher Copyright: {\textcopyright} 2022 International Medical Informatics Association (IMIA) and IOS Press.; 18th World Congress on Medical and Health Informatics: One World, One Health - Global Partnership for Digital Innovation, MEDINFO 2021 ; Conference date: 02-10-2021 Through 04-10-2021",
year = "2022",
month = jun,
day = "6",
doi = "10.3233/SHTI220180",
language = "English (US)",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "757--761",
editor = "Paula Otero and Philip Scott and Martin, {Susan Z.} and Elaine Huesing",
booktitle = "MEDINFO 2021",
address = "Netherlands",
}