Generating high-quality data abstractions from scanned clinical records: text-mining-assisted extraction of endometrial carcinoma pathology features as proof of principle

OBJECTIVE: Medical research studies often rely on the manual collection of data from scanned typewritten clinical records, which can be laborious, time consuming and error prone because of the need to review individual clinical records. We aimed to use text mining to assist with the extraction of cl...

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Detalles Bibliográficos
Autores principales: Nguyen, Anthony, O'Dwyer, John, Vu, Thanh, Webb, Penelope M, Johnatty, Sharon E, Spurdle, Amanda B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Health Informatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295399/
https://www.ncbi.nlm.nih.gov/pubmed/32532784
http://dx.doi.org/10.1136/bmjopen-2020-037740

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295399/
https://www.ncbi.nlm.nih.gov/pubmed/32532784
http://dx.doi.org/10.1136/bmjopen-2020-037740

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