HRS Bibliography
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Filters: Keyword is Machine learning [Clear All Filters]
2024
Regressive class models for machine learning algorithms to predict trajectories of repeated multinomial outcomes: an application to the activity of daily living of elderly data. Communications in Statistics: Simulation and Computation. 2024. doi:10.1080/03610918.2024.2311774.
. 2023
Predictive Models of Life Satisfaction in Older People: A Machine Learning Approach. Int J Environ Res Public Health. 2023;20(3). doi:10.3390/ijerph20032445.
. 2022
Consistent and robust predictors of Internet Use among older adults over time identified by machine learning. Computers in Human Behavior. 2022;137:107413. doi:https://doi.org/10.1016/j.chb.2022.107413.
. Determinants of COVID-19 Outcome as Predictors of Delayed Healthcare Services among Adults ≥50 Years during the Pandemic: 2006–2020 Health and Retirement Study. IJERPH. 2022;19:1-24.
EXAMINING THE MULTIMORBIDITY PROFILE OF MIDLIFE AND OLDER ADULTS WITH DIABETES USING MACHINE LEARNING. 2022;Ph.D.
. Health State Risk Categorization: A Machine Learning Clustering Approach Using Health and Retirement Study Data. The Journal of Financial Data Science. 2022;4(2):139–167. doi:10.3905/jfds.2022.4.2.139.
. . 2021
Finding Needles in Haystacks: Multiple-Imputation Record Linkage Using Machine Learning. United State Census Bureau; 2021.
Healthy memory aging - the benefits of regular daily activities increase with age. Aging. 2021;13(24):25643-25652. doi:10.18632/aging.203753.
. Statistical Significance of Hyperparameter Tuning for Varying Levels of Class Imbalance. In: 26th ISSAT International Conference on Reliability and Quality in Design, RQD 2021. 26th ISSAT International Conference on Reliability and Quality in Design, RQD 2021. ; 2021.
. 2020
Development of Algorithmic Dementia Ascertainment for Racial/Ethnic Disparities Research in the US Health and Retirement Study. Epidemiology. 2020;31(1):126-133. doi:10.1097/EDE.0000000000001101.
. Investigating predictors of cognitive decline using machine learning. Journals of Gerontology, Series B: Psychological Sciences & Social Sciences. 2020. doi:10.1093/geronb/gby054.
. http://www.ncbi.nlm.nih.gov/pubmed/29718387?dopt=Abstract
Predicting Cognitive Impairment and Dementia: A Machine Learning Approach. Journal of Alzheimer's disease : JAD. 2020;75(3):717-728. doi:10.3233/JAD-190967.
2018
Machine learning approaches to the social determinants of health in the Health and Retirement study. SSM Popul Health. 2018;4:95-99. doi:10.1016/j.ssmph.2017.11.008.
. http://www.ncbi.nlm.nih.gov/pubmed/29349278?dopt=Abstract
Unsupervised Machine Learning to Identify High Likelihood of Dementia in Population-Based Surveys: Development and Validation Study. Journal of Medical Internet Research. 2018;20(7):e10493. doi:10.2196/10493.
. http://www.ncbi.nlm.nih.gov/pubmed/29986849?dopt=Abstract
2017
Identifying Specific Combinations of Multimorbidity that Contribute to Health Care Resource Utilization: An Analytic Approach. Med Care. 2017;55(3):276-284. doi:10.1097/MLR.0000000000000660.
http://www.ncbi.nlm.nih.gov/pubmed/27753745?dopt=Abstract
A machine-learning heuristic to improve gene score prediction of polygenic traits. Scientific Reports. 2017;7(1):12665. doi:10.1038/s41598-017-13056-1.
. http://www.ncbi.nlm.nih.gov/pubmed/28979001?dopt=Abstract