R/Medicine 2025
The R/Medicine conference provides a forum for sharing R based tools and approaches used to analyze and gain insights from health data
Attendees#
Featured software#
Resources from this event#
Personal R Administration
From R/Medicine 2025
– Does the release of a new R version fill you with dread? – Are there passwords in your R code? – Do you look at the output of a failed package installation and think to yourself, “WTF?!”
If you said yes to any of those questions, then you need Personal R Administration. You’ll come away with tips, tricks, tweaks, and some hacks for building data science dev environments that you won’t be afraid to come back to in a year.
David Aja and Shannon Pileggi
E. David Aja is a Software Engineer at Posit. Before joining Posit, he worked as a data scientist in the public sector.
Shannon Pileggi (she/her) is a Lead Data Scientist at The Prostate Cancer Clinical Trials Consortium, a frequent blogger, and a member of the R-Ladies Global leadership team. She enjoys automating data wrangling and data outputs, and making both data insights and learning new material digestible.
Resources
R/Medicine: https://rconsortium.github.io/RMedicine_website/ R Consortium: https://www.r-consortium.org/
Quarto Dashboards: from zero to publish in one hour
From R/Medicine 2025
You already analyze and summarize your data with R and Quarto. What’s next?
You can share your insights or allow others to make their own conclusions in eye-catching dashboards and straight-forward to author, design, and deploy Quarto Dashboards. With Quarto Dashboards, you can create elegant and production-ready dashboards using a variety of components, including static graphics, interactive widgets, tabular data, value boxes, text annotations, and more.
Additionally, with intelligent resizing of components, your Quarto Dashboards look great on devices of all sizes. And importantly, you can author Quarto Dashboards without leaving the comfort of your “home” – in plain text markdown with any text editor. In this one-hour demo we will build and publish a Quarto Dashboard – you can code-along or sit back and enjoy the show!
Mine Çetinkaya-Rundel, Professor of the Practice at Duke University and Developer Educator at Posit
Mine’s work focuses on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education as well as pedagogical approaches for enhancing retention of women and under-represented minorities in STEM.
Mine works on the OpenIntro project, whose mission is to make educational products that are free, transparent, and lower barriers to education. As part of this project she co-authored four open-source introductory statistics textbooks – latest is the 2nd edition of Introduction to Modern Statistics.
She is also a co-author on R for Data Science, the creator and maintainer of Data Science in a Box, and she teaches popular data analysis and data science with R courses on Coursera. Mine is a Fellow of the ASA and Elected Member of the ISI as well as a Waller and Hogg award winner for teaching excellence. In 2024, she was elected as Vice President of the International Association for Statistical Education (IASE).
Resources R/Medicine: https://rconsortium.github.io/RMedicine_website/ R Consortium: https://www.r-consortium.org/
Demystifying LLMs with Ellmer
From R/Medicine 2025
Joe Cheng, CTO, Posit Joe Cheng is the CTO of Posit, PBC. He’s the original creator of the Shiny web framework and co-creator of ellmer.
Today’s best LLMs are incredibly powerful–but you’re only scratching the surface of their capabilities if your use is limited to ChatGPT or Copilot. Accessing LLMs programmatically opens up a whole new world of possibilities, letting you integrate LLMs into your own apps, scripts, and workflows. In this workshop, we’ll cover:
A practical introduction to LLM APIs
– Configuring R to access LLMs via the ellmer package – Customizing LLM behavior using system prompts and tool calling – Creating Shiny apps with integrated chatbots – Using LLMs for natural language processing
Attendees will leave the workshop armed with ready-to-run examples, and the confidence and inspiration to run their own experiments with LLMs.
Attendees should be familiar with the basics of R and have a working R installation.
Note that to avoid any potential firewall issues, it is recommended that participants use a personal computer for this workshop.
Resources
Presentation: https://jcheng5.github.io/rmedicine-2025 R/Medicine: https://rconsortium.github.io/RMedicine_website/ R Consortium: https://www.r-consortium.org/
