Inclusion of a multi-ancestry polygenic risk score into a machine learning weight gain prediction model: an observational analysis from the NIH All of Us Research Program
- DOI
- 10.1093/jamiaopen/ooag205
- Published
- 2026-09-09
- Container
- JAMIA Open
- Publisher
- Oxford University Press (OUP)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1093/jamiaopen/ooag205,
title = {Inclusion of a multi-ancestry polygenic risk score into a machine learning weight gain prediction model: an observational analysis from the NIH All of Us Research Program},
author = {Kate V Lauer and Lily N Stalter and Bret M Hanlon and Brian W Parks and Tianyuan Lu and Luke M Funk},
year = {2026},
journal = {JAMIA Open},
doi = {10.1093/jamiaopen/ooag205},
url = {https://doi.org/10.1093/jamiaopen/ooag205}
}RIS
TY - JOUR TI - Inclusion of a multi-ancestry polygenic risk score into a machine learning weight gain prediction model: an observational analysis from the NIH All of Us Research Program AU - Kate V Lauer AU - Lily N Stalter AU - Bret M Hanlon AU - Brian W Parks AU - Tianyuan Lu AU - Luke M Funk PY - 2026 JO - JAMIA Open DO - 10.1093/jamiaopen/ooag205 UR - https://doi.org/10.1093/jamiaopen/ooag205 ER -
APA
Lauer, K. V., Stalter, L. N., Hanlon, B. M., Parks, B. W., Lu, T., & Funk, L. M. (2026). Inclusion of a multi-ancestry polygenic risk score into a machine learning weight gain prediction model: an observational analysis from the NIH All of Us Research Program. JAMIA Open. https://doi.org/10.1093/jamiaopen/ooag205
Source records
- crossref · retrieved 2026-11-08T10:25:45.602Z