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Viewing 2 past events matching “public health” by Date.
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Tuesday
May 6, 2014
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Nerd Nite Portland #15 – I Will Revive: Using Naloxone to Reverse Overdoses – Mission Theater Nerd Nite is a monthly event that strives for an inebriated, salacious, yet soundly academic vibe. We aim to entertain, educate, elucidate, enlighten, and other things that start with “e.” Be there and be square. When: Tuesday, May 6, 2014, doors at 6:00pm, event at 7:00pm Cost: $8.00* suggested cover at the door This Nerd Nite will feature several speakers on one topic. Oregon has one of the highest rates in the country for illicit use of prescription opiates. Overdose deaths rose 400 percent from 2000 to 2011. But since last July, naloxone – a drug long used by emergency medical personnel to reverse an opiate overdose – has been made available to trained lay people and more than 600 people have been trained in how to use the drug. Meet the men and women from the Multnomah County Health Department and Outside In as they discuss what naloxone is, what it does, and how it has already saved more than 200 lives. *A note on the suggested cover: Nerd Nite is completely supported by money collected at the door. We are committed to offering education opportunities to adults who want to learn, so if $8 is a hardship for you, please come anyway and donate what you can. |
Monday
Feb 13, 2017
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pdxrlang meetup: Text mining & association rule mining in R to enhance public health surveillance – WeWork Custom House 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. |