1. Leveraging language data in healthcare (by Robyn Ball)
   —
   Many critical questions in healthcare can only be answered by combining structured and unstructured data. Language data is the most rich and high-valued data in healthcare, yet it often is underutilized due to the complexity of developing natural language models that can extract meaningful insights. I will provide a brief overview of using NLP in the healthcare, describe Roam's general framework, and provide datasets and other resources that can be used to jump-start research projects.

Bio:
Dr. Robyn Ball is a Clinical Data Scientist at Roam Analytics, where she leverages Roam’s data and machine learning assets to create analyses of patient pathways through disease and treatment progression. Dr. Ball earned her Ph.D. in Statistics from Texas A&M University. She has conducted biomedical research as a NASA fellow and as an intern at UT MD Anderson Cancer Center, developed novel computational methods for genomic data at The Jackson Laboratory in Bar Harbor, Maine, and was most recently a Senior Biostatistician at Stanford University where she collaborated with medical researchers on studies that posed methodological challenges.

2. Functions, Packages and Visualization in R: a case study using 'cholera' (by Peter Li)
   —
   John Snow's map of the 1854 cholera outbreak in London's Soho is a classic example of data visualization. For Snow, the map served as support of his two then contested, if not controversial claims: that cholera is a waterborne disease and that the water pump on Broad Street was the source of the outbreak.
   To evaluate whether the map does or can support such claims, I've been developing the R 'cholera' package (CRAN and GitHub). By allowing you to compute and plot pump neighborhoods, sets of homes defined by their proximity to a pump, the package allows you to explore, analyze and test the data embedded in the map.
   This will be a hands-on, interactive session. There are three objectives: to introduce new techniques, and new applications of familiar techniques; to inspire you to write your own functions and packages; to put the spotlight on the science half of data science.

Bio:
Peter Li is a quantitative social scientist and long time R user.

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AGENDA (preliminary):
5:30pm - 6pm: Help with the setup (install R packages and anything else that is needed for the workshop)
6pm - 6:20pm: Networking
6:20pm - 6:45pm: Talk#1
6:45pm - 7:45pm: Talk#2
7:45pm - 8pm: Networking

• There is parking located behind the building on Palm Avenue.

• For those who will be taking public transportation, we will be providing complimentary transportation from Caltrain and BART via shuttles. For those heading Southbound from San Francisco, there will be a shuttle at the Milbrae BART Station. For those heading Northbound, there is a shuttle at the Hillsdale CalTrain Station. MAKE SURE TO FILL THIS OUT: https://goo.gl/forms/YMyyFRiCgPRZ3LaC2

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• Important to know

CODE OF CONDUCT
Anyone who violates or has previously violated this community's Code of Conduct will be refused entry, expelled, and/or any other action deemed appropriate by the Organizer, regardless of event registration, meetup membership or other condition.
https://github.com/rladies/starter-kit/wiki/Code-of-Conduct

• The mission of R-Ladies is to achieve proportionate representation by encouraging, inspiring, and empowering people of genders currently underrepresented in the R community.

We are emphatically queer and trans-friendly.

• Refreshments and food will be provided.

A huge thank you to Roam (https://roamanalytics.com/) for hosting us!