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Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores.
Hrytsenko Y, Shea B, Elgart M, Kurniansyah N, Lyons G, Morrison AC, Carson AP, Haring B, Mitchel BD, Psaty BM, Jaeger BC, Gu CC, Kooperberg C, Levy D, Lloyd-Jones D, Choi E, Brody JA, Smith JA, Rotter JI, Moll M, Fornage M, Simon N, Castaldi P, Casanova R, Chung RH, Kaplan R, Loos RJF, Kardia SLR, Rich SS, Redline S, Kelly T, O'Connor T, Zhao W, Kim W, Guo X, Der Ida Chen Y; Trans-Omics in Precision Medicine Consortium; Sofer T. Hrytsenko Y, et al. medRxiv [Preprint]. 2023 Dec 14:2023.12.13.23299909. doi: 10.1101/2023.12.13.23299909. medRxiv. 2023. PMID: 38168328 Free PMC article. Preprint.
Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.
Hrytsenko Y, Shea B, Elgart M, Kurniansyah N, Lyons G, Morrison AC, Carson AP, Haring B, Mitchell BD, Psaty BM, Jaeger BC, Gu CC, Kooperberg C, Levy D, Lloyd-Jones D, Choi E, Brody JA, Smith JA, Rotter JI, Moll M, Fornage M, Simon N, Castaldi P, Casanova R, Chung RH, Kaplan R, Loos RJF, Kardia SLR, Rich SS, Redline S, Kelly T, O'Connor T, Zhao W, Kim W, Guo X, Ida Chen YD; Trans-Omics in Precision Medicine Consortium; Sofer T. Hrytsenko Y, et al. Sci Rep. 2024 May 30;14(1):12436. doi: 10.1038/s41598-024-62945-9. Sci Rep. 2024. PMID: 38816422 Free PMC article.