Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision

Most detailed patient information in real-world data (RWD) is only consistently available in free-text clinical documents. Manual curation is expensive and time consuming. Developing natural language processing (NLP) methods for structuring RWD is thus essential for scaling real-world evidence gener...

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Detalles Bibliográficos
Autores principales: Preston, Sam, Wei, Mu, Rao, Rajesh, Tinn, Robert, Usuyama, Naoto, Lucas, Michael, Gu, Yu, Weerasinghe, Roshanthi, Lee, Soohee, Piening, Brian, Tittel, Paul, Valluri, Naveen, Naumann, Tristan, Bifulco, Carlo, Poon, Hoifung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10140604/
https://www.ncbi.nlm.nih.gov/pubmed/37123439
http://dx.doi.org/10.1016/j.patter.2023.100726

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10140604/
https://www.ncbi.nlm.nih.gov/pubmed/37123439
http://dx.doi.org/10.1016/j.patter.2023.100726

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