Appendicular Skeletal Muscle Mass in Older Adults Can Be Estimated With a Simple Equation Using a Few Zero-Cost Variables

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@Article{Buccheri:2024:JPT,

• author = "Enrico Buccheri and Daniele Dell'Aquila and Marco Russo and Rita Chiaramonte and Michele Vecchio",
• title = "Appendicular Skeletal Muscle Mass in Older Adults Can Be Estimated With a Simple Equation Using a Few Zero-Cost Variables",
• journal = "Journal of Geriatric Physical Therapy",
• year = "2024",
• volume = "47",
• number = "4",
• pages = "E149--E158",
• month = oct # "/" # dec,
• keywords = "genetic algorithms, genetic programming, Brain Project, medicine, appendicular skeletal muscle mass, artificial intelligence, dual-energy X-ray absorptiometer, muscle mass loss",
• URL = "https://pubmed.ncbi.nlm.nih.gov/39079022/",
• DOI = "doi:10.1519/JPT.0000000000000420",
• size = "10 pages",
• notes = "Supplemental digital contents are available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.jgptonline.com)

  Department of Biomedical and Biotechnological Sciences, Section of Pharmacology, University of Catania, Catania, Italy.",

}

Genetic Programming entries for Enrico Buccheri Daniele Dell'Aquila Marco Russo Rita Chiaramonte Michele Vecchio

Citations