Dietary profiling of physical frailty in older age phenotypes using a machine learning approach: the Salus in Apulia Study

  • Home/
  • Dietary profiling of physical frailty in older age phenotypes using a machine learning approach: the Salus in Apulia Study

Dietary profiling of physical frailty in older age phenotypes using a machine learning approach: the Salus in Apulia Study

European Journal of Nutrition (Springer - 2023) - -2023

Authors

De Nucci Sara, Zupo Roberta, Donghia Rossella, Castellana Fabio, Lofù Domenico, Aresta Simona, Guerra Vito, Bortone Ilaria, Lampignano Luisa, De Pergola Giovanni, Lozupone Madia, Tatoli Rossella, Sborgia Giancarlo, Tirelli Sarah, Panza Francesco, Di Noia Tommaso, Sardone Rodolfo

DOI

https://doi.org/10.1007/s00394-023-03174-0

BibTex references

@Article{DZDCLAGBLDLTSTPDS23,
  author       = "De Nucci, Sara and Zupo, Roberta and Donghia, Rossella and Castellana, Fabio and Lof\`u, Domenico and Aresta, Simona and Guerra, Vito and Bortone, Ilaria and Lampignano, Luisa and De Pergola, Giovanni and Lozupone, Madia and Tatoli, Rossella and Sborgia, Giancarlo and Tirelli, Sarah and Panza, Francesco and Di Noia, Tommaso and Sardone, Rodolfo",
  title        = "Dietary profiling of physical frailty in older age phenotypes using a machine learning approach: the Salus in Apulia Study",
  journal      = "European Journal of Nutrition (Springer - 2023)",
  volume       = "62",
  pages        = "1217-1229",
  year         = "2023",
  url          = "http://sisinflab.poliba.it/Publications/2023/DZDCLAGBLDLTSTPDS23"

}