BEGIN:VCALENDAR PRODID;X-RICAL-TZSOURCE=TZINFO:-//Calagator//EN CALSCALE:GREGORIAN X-WR-CALNAME:Calagator METHOD:PUBLISH VERSION:2.0 BEGIN:VTIMEZONE TZID;X-RICAL-TZSOURCE=TZINFO:America/Los_Angeles BEGIN:STANDARD DTSTART:20161106T020000 RDATE:20161106T020000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST END:STANDARD END:VTIMEZONE BEGIN:VEVENT CREATED;VALUE=DATE-TIME:20170110T181640Z DTEND;TZID=America/Los_Angeles;VALUE=DATE-TIME:20170213T200000 DTSTART;TZID=America/Los_Angeles;VALUE=DATE-TIME:20170213T183000 DTSTAMP;VALUE=DATE-TIME:20170110T181640Z LAST-MODIFIED;VALUE=DATE-TIME:20170110T181640Z UID:http://calagator.org/events/1250471314 DESCRIPTION:Speaker: Matt Laidler \;\n \;\nAbstract: R can be a po werful tool for the process of systematically tracking health-related ou tcomes (i.e. surveillance) identified from administrative data sources. Tracking health outcomes in populations often relies on coded administra tive data to standardize metrics and simplify processes. This may have t he 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 te xt mining and association rule mining in R for tracking health outcomes. \n\nTags: pdxrlang\, r\, rstats\, programming\, text-mining\, public hea lth\n\nImported from: http://calagator.org/events/1250471314 URL:https://www.meetup.com/portland-r-user-group/events/236703908/ SUMMARY:pdxrlang meetup: Text mining & association rule mining in R to en hance public health surveillance LOCATION:WeWork Custom House: 220 Northwest 8th Avenue\, Portland OR 9720 9 US SEQUENCE:1 END:VEVENT END:VCALENDAR