@inproceedings{87e9f8d1d5524f51823db2ea78acdc0d,
title = "Early Alert of Elderly Cognitive Impairment using Temporal Streaming Clustering",
abstract = "more than 44 million people have been diagnosed with dementia worldwide, and this number is estimated to triple by next three decades. Given this increasing trend of older adults with cognitive impairment (CI; dementia and mild cognitive impairment) and its significant underdiagnosis, early identification of CI and understanding its progression is a critical step towards a better quality of life for the aging population. Early alert of individual health changes could facilitate better ways for clinicians to diagnose CI in its early stages and come up with more effective treatment plans. However, there is a lack of approaches to characterize patient health conditions accounting for temporal information in an unsupervised manner. Limited CI cases and its costly ascertainment in clinical settings also make unsupervised learning more promising in CI research. In this paper, a streaming clustering model was used to determine distinct patterns of older adults' health changes from their clinical visits in Mayo Clinic Study of Aging. The streaming clustering was also examined to study its ability to generate early alerts for potential incidents of CI. Our analysis demonstrated that temporal characteristics incorporated in a streaming clustering model has a promising potential to increase power in predicting CI.",
keywords = "dementia, mild cognitive impairment, prediction, streaming clustering",
author = "Ibrahim, {Omar A.} and Sunyang Fu and Maria Vassilaki and Petersen, {Ronald C.} and Mielke, {Michelle M.} and Sauver, {Jennifer St} and Sunghwan Sohn",
note = "Funding Information: ACKNOWLEDGMENT 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. Ronald C. Petersen – Consultant for Roche, Inc., Biogen, Inc., Merck, Inc., Eli Lilly and Company, and Genentech, Inc.; receives publishing royalties from Mild Cognitive Impairment (Oxford University Press, 2003), and receives research support from the National Institute of Health. Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 ; Conference date: 09-12-2021 Through 12-12-2021",
year = "2021",
doi = "10.1109/BIBM52615.2021.9669672",
language = "English (US)",
series = "Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "905--912",
editor = "Yufei Huang and Lukasz Kurgan and Feng Luo and Hu, {Xiaohua Tony} and Yidong Chen and Edward Dougherty and Andrzej Kloczkowski and Yaohang Li",
booktitle = "Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021",
}