A comprehensive tool for creating and evaluating privacy-preserving biomedical prediction models

BACKGROUND: Modern data driven medical research promises to provide new insights into the development and course of disease and to enable novel methods of clinical decision support. To realize this, machine learning models can be trained to make predictions from clinical, paraclinical and biomolecul...

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Detalles Bibliográficos
Autores principales: Eicher, Johanna, Bild, Raffael, Spengler, Helmut, Kuhn, Klaus A., Prasser, Fabian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014648/
https://www.ncbi.nlm.nih.gov/pubmed/32046701
http://dx.doi.org/10.1186/s12911-020-1041-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014648/
https://www.ncbi.nlm.nih.gov/pubmed/32046701
http://dx.doi.org/10.1186/s12911-020-1041-3

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