Scalable and accurate deep learning with electronic health records

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variables from normalized EHR data, a labor-intensive process that...

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Detalles Bibliográficos
Autores principales: Rajkomar, Alvin, Oren, Eyal, Chen, Kai, Dai, Andrew M., Hajaj, Nissan, Hardt, Michaela, Liu, Peter J., Liu, Xiaobing, Marcus, Jake, Sun, Mimi, Sundberg, Patrik, Yee, Hector, Zhang, Kun, Zhang, Yi, Flores, Gerardo, Duggan, Gavin E., Irvine, Jamie, Le, Quoc, Litsch, Kurt, Mossin, Alexander, Tansuwan, Justin, Wang, De, Wexler, James, Wilson, Jimbo, Ludwig, Dana, Volchenboum, Samuel L., Chou, Katherine, Pearson, Michael, Madabushi, Srinivasan, Shah, Nigam H., Butte, Atul J., Howell, Michael D., Cui, Claire, Corrado, Greg S., Dean, Jeffrey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550175/
https://www.ncbi.nlm.nih.gov/pubmed/31304302
http://dx.doi.org/10.1038/s41746-018-0029-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550175/
https://www.ncbi.nlm.nih.gov/pubmed/31304302
http://dx.doi.org/10.1038/s41746-018-0029-1

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