Artificial intelligence-aided clinical annotation of a large multi-cancer genomic dataset

To accelerate cancer research that correlates biomarkers with clinical endpoints, methods are needed to ascertain outcomes from electronic health records at scale. Here, we train deep natural language processing (NLP) models to extract outcomes for participants with any of 7 solid tumors in a precis...

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Detalles Bibliográficos
Autores principales: Kehl, Kenneth L., Xu, Wenxin, Gusev, Alexander, Bakouny, Ziad, Choueiri, Toni K., Riaz, Irbaz Bin, Elmarakeby, Haitham, Van Allen, Eliezer M., Schrag, Deborah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8674229/
https://www.ncbi.nlm.nih.gov/pubmed/34911934
http://dx.doi.org/10.1038/s41467-021-27358-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8674229/
https://www.ncbi.nlm.nih.gov/pubmed/34911934
http://dx.doi.org/10.1038/s41467-021-27358-6

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