Natural language processing of radiology reports for the detection of thromboembolic diseases and clinically relevant incidental findings

BACKGROUND: Natural Language Processing (NLP) has been shown effective to analyze the content of radiology reports and identify diagnosis or patient characteristics. We evaluate the combination of NLP and machine learning to detect thromboembolic disease diagnosis and incidental clinically relevant...

Descripción completa

Detalles Bibliográficos
Autores principales: Pham, Anne-Dominique, Névéol, Aurélie, Lavergne, Thomas, Yasunaga, Daisuke, Clément, Olivier, Meyer, Guy, Morello, Rémy, Burgun, Anita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4133634/
https://www.ncbi.nlm.nih.gov/pubmed/25099227
http://dx.doi.org/10.1186/1471-2105-15-266

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4133634/
https://www.ncbi.nlm.nih.gov/pubmed/25099227
http://dx.doi.org/10.1186/1471-2105-15-266

Ejemplares similares