Comparing Rule-based, Feature-based and Deep Neural Methods for De-identification of Dutch Medical Records

Trienes Jan, Dolf Trienschnigg, Christin Seifert, Djoerd Hiemstra

Research output: Contribution to conferencePaper

34 Downloads (Pure)
Original languageEnglish
Publication statusPublished - 2020
EventACM Health Search and Data Mining Workshop, HSDM 2020 - Houston, United States
Duration: 3 Feb 20203 Feb 2020
https://sites.google.com/view/hsdm20

Workshop

WorkshopACM Health Search and Data Mining Workshop, HSDM 2020
Abbreviated titleHSDM 2020
CountryUnited States
CityHouston
Period3/02/203/02/20
OtherHeld at the 13th ACM International WSDM Conference
Internet address

Cite this

Jan, T., Trienschnigg, D., Seifert, C., & Hiemstra, D. (2020). Comparing Rule-based, Feature-based and Deep Neural Methods for De-identification of Dutch Medical Records. Paper presented at ACM Health Search and Data Mining Workshop, HSDM 2020, Houston, United States.