Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records

Secondary use of electronic health records (EHRs) promises to advance clinical research and better inform clinical decision making. Challenges in summarizing and representing patient data prevent widespread practice of predictive modeling using EHRs. Here we present a novel unsupervised deep feature...

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Detalles Bibliográficos
Autores principales: Miotto, Riccardo, Li, Li, Kidd, Brian A., Dudley, Joel T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869115/
https://www.ncbi.nlm.nih.gov/pubmed/27185194
http://dx.doi.org/10.1038/srep26094

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869115/
https://www.ncbi.nlm.nih.gov/pubmed/27185194
http://dx.doi.org/10.1038/srep26094

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