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Fracture risk prediction in postmenopausal women with traditional and machine learning models in a nationwide, prospective cohort study in Switzerland with validation in the UK Biobank.

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Title: Fracture risk prediction in postmenopausal women with traditional and machine learning models in a nationwide, prospective cohort study in Switzerland with validation in the UK Biobank.
Authors: Lehmann, Oliver1 (AUTHOR) ollehman@student.ethz.ch, Mineeva, Olga2 (AUTHOR) olga.mineeva@inf.ethz.ch, Veshchezerova, Dinara3 (AUTHOR) dinara.veshchezerova@grlab.org, Häuselmann, HansJörg3 (AUTHOR) hjhauselmann@rheumazentrum.ch, Guyer, Laura4 (AUTHOR) laura.guyer@hispeed.ch, Reichenbach, Stephan5,6 (AUTHOR) stephan.reichenbach@ispm.unibe.ch, Lehmann, Thomas7 (AUTHOR) lehmann@hin.ch, Demler, Olga3,8 (AUTHOR) odemler@bwh.harvard.edu, Everts-Graber, Judith7,8,9 (AUTHOR) judith.everts@hin.ch, Wenger, Mathias (AUTHOR), Oser, Sven (AUTHOR), Toniolo, Martin (AUTHOR), Schmid, Gernot (AUTHOR), Studer, Ueli (AUTHOR), Ziswiler, Hans-Rudolf (AUTHOR), Steiner, Christian (AUTHOR), Krappel, Ferdinand (AUTHOR), Pancaldi, Piero (AUTHOR), Kashiwagi, Maki (AUTHOR), Frey, Diana (AUTHOR)
Source: Journal of Bone & Mineral Research. Aug2024, Vol. 39 Issue 8, p1103-1112.
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