Natural language processing and recurrent network models for identifying genomic mutation-associated cancer treatment change from patient progress notes

OBJECTIVES: Natural language processing (NLP) and machine learning approaches were used to build classifiers to identify genomic-related treatment changes in the free-text visit progress notes of cancer patients. METHODS: We obtained 5889 deidentified progress reports (2439 words on average) for 755...

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Detalles Bibliográficos
Autores principales: Guan, Meijian, Cho, Samuel, Petro, Robin, Zhang, Wei, Pasche, Boris, Topaloglu, Umit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Research and Applications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6435007/
https://www.ncbi.nlm.nih.gov/pubmed/30944913
http://dx.doi.org/10.1093/jamiaopen/ooy061

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6435007/
https://www.ncbi.nlm.nih.gov/pubmed/30944913
http://dx.doi.org/10.1093/jamiaopen/ooy061

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