Selection bias in the reported performances of AD classification pipelines

The last decade has seen a great proliferation of supervised learning pipelines for individual diagnosis and prognosis in Alzheimer's disease. As more pipelines are developed and evaluated in the search for greater performance, only those results that are relatively impressive will be selected...

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Detalles Bibliográficos
Autores principales: Mendelson, Alex F., Zuluaga, Maria A., Lorenzi, Marco, Hutton, Brian F., Ourselin, Sébastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Regular Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322215/
https://www.ncbi.nlm.nih.gov/pubmed/28271040
http://dx.doi.org/10.1016/j.nicl.2016.12.018

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322215/
https://www.ncbi.nlm.nih.gov/pubmed/28271040
http://dx.doi.org/10.1016/j.nicl.2016.12.018

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