Modelling menstrual cycle length in athletes using state-space models

The ability to predict an individual’s menstrual cycle length to a high degree of precision could help female athletes to track their period and tailor their training and nutrition correspondingly. Such individualisation is possible and necessary, given the known inter-individual variation in cycle...

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Detalles Bibliográficos
Autores principales: de Paula Oliveira, Thiago, Bruinvels, Georgie, Pedlar, Charles R, Moore, Brian, Newell, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379295/
https://www.ncbi.nlm.nih.gov/pubmed/34417493
http://dx.doi.org/10.1038/s41598-021-95960-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379295/
https://www.ncbi.nlm.nih.gov/pubmed/34417493
http://dx.doi.org/10.1038/s41598-021-95960-1

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