Deep representation learning of electronic health records to unlock patient stratification at scale

Deriving disease subtypes from electronic health records (EHRs) can guide next-generation personalized medicine. However, challenges in summarizing and representing patient data prevent widespread practice of scalable EHR-based stratification analysis. Here we present an unsupervised framework based...

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Detalles Bibliográficos
Autores principales: Landi, Isotta, Glicksberg, Benjamin S., Lee, Hao-Chih, Cherng, Sarah, Landi, Giulia, Danieletto, Matteo, Dudley, Joel T., Furlanello, Cesare, Miotto, Riccardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367859/
https://www.ncbi.nlm.nih.gov/pubmed/32699826
http://dx.doi.org/10.1038/s41746-020-0301-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367859/
https://www.ncbi.nlm.nih.gov/pubmed/32699826
http://dx.doi.org/10.1038/s41746-020-0301-z

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