Text mining & association rule mining in R to enhance public health surveillance

Hosted by Portland R User Group

Public group


Speaker: Matt Laidler

Abstract: R can be a powerful tool for the process of systematically tracking health-related outcomes (i.e. surveillance) identified from administrative data sources. Tracking health outcomes in populations often relies on coded administrative data to standardize metrics and simplify processes. This may have the effect of overlooking useful information described in free text data, but due to data volume/size, may not be practical to process outside of text mining methods. This presentation will describe a use case of text mining and association rule mining in R for tracking health outcomes.


Enter on West side of building through metal gates. Gates may be open, but if closed a security guard will be present to let you in.

Doors open at 615 pm. DO NOT SHOW UP BEFORE 615 PM. Talk starts at 6:30 pm. Repeat: DO NOT SHOW UP BEFORE 615 PM. We'll visit a local watering hole afterwards.

Propose a talk! Or suggest a talk you want to hear or attend: https://sckott.typeform.com/to/ShM55K

Hashtag for PDX R meetups: #pdxrlang & the Twitter account to follow/tweet at is @pdxrlang

We also use http://pdxdata.slack.com/ for a back-channel during MeetUps and in between. Invite yourself here: http://pdxdata.org/slack/