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Explaining predictive factors in patient pathways using autoencoders
This paper introduces an end-to-end methodology to predict a pathway-related outcome and identifying predictive factors using autoencoders. A formal description of autoencoders for explainable binary predictions is presented, along with two objective functions that allows for filtering and inverting...
Autores principales: | De Oliveira, Hugo, Martin, Prodel, Ludovic, Lamarsalle, Vincent, Augusto, Xiaolan, Xie |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648714/ https://www.ncbi.nlm.nih.gov/pubmed/36355757 http://dx.doi.org/10.1371/journal.pone.0277135 |
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