HRS Bibliography

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2021

Abowd JM, Abramowitz J, Levenstein MC, et al. Finding Needles in Haystacks: Multiple-Imputation Record Linkage Using Machine Learning. United State Census Bureau; 2021.
Krakovska O, Christie GJ, Farzan F, Sixsmith A, Ester M, Moreno S. Healthy memory aging - the benefits of regular daily activities increase with age. Aging. 2021;13(24):25643-25652. doi:10.18632/aging.203753.
Hancock J, Khoshgoftaar TM, Landset S. 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

Gianattasio KZ, Ciarleglio A, Power MC. 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.
Casanova R, Saldana S, Lutz MW, Plassman BL, Kuchibhatla M, Hayden KM. 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
Aschwanden D, Aichele S, Ghisletta P, et al. 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

Seligman B, Tuljapurkar S, Rehkopf D. 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
de Langavant LCleret, Bayen E, Yaffe K. 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

Schiltz NK, Warner DF, Sun J, et al. 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
Pare G, Mao S, Deng WQ. 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