Toward Complete Structured Information Extraction from Radiology Reports Using Machine Learning

Unstructured and semi-structured radiology reports represent an underutilized trove of information for machine learning (ML)-based clinical informatics applications, including abnormality tracking systems, research cohort identification, point-of-care summarization, semi-automated report writing, an...

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Detalles Bibliográficos
Autores principales: Steinkamp, Jackson M., Chambers, Charles, Lalevic, Darco, Zafar, Hanna M., Cook, Tessa S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646440/
https://www.ncbi.nlm.nih.gov/pubmed/31218554
http://dx.doi.org/10.1007/s10278-019-00234-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646440/
https://www.ncbi.nlm.nih.gov/pubmed/31218554
http://dx.doi.org/10.1007/s10278-019-00234-y

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