Age and life expectancy clocks based on machine learning analysis of mouse frailty

The discovery of interventions that slow aging could be accelerated by employing non-invasive biometrics that predict biological age or life expectancy. Here the authors use longitudinal frailty data from naturally aging mice to develop two such tools, that are responsive to interventions.

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Autores principales: Michael B. Schultz, Alice E. Kane, Sarah J. Mitchell, Michael R. MacArthur, Elisa Warner, David S. Vogel, James R. Mitchell, Susan E. Howlett, Michael S. Bonkowski, David A. Sinclair
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/3a49ccbd63f44865818e20ab50fb5065
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