About
The goal of the R/Medicine conference is to promote the use of the R programming environment and the R ecosystem in medical research and clinical practice. R, the open source language for statistical computing and data visualization, has also become an effective tool for enabling reproducible research and the communication of scientific knowledge. In addition to showcasing novel tools, algorithms and methods for analyzing medical and clinical data. We hope the conference will provide a forum for collaboration within the community.
Conference talks will address the use of R in medical applications from Phase I clinical trial design through the analysis of the efficacy of medical therapies in public use. Topic areas for R/Medicine include: clinical trial design, the analysis of clinical trial data, personalized medicine, the analysis of patient records, the analysis of genetic data, the visualization of medical data, and reproducible research.
Note that topics related to drug discovery and PK/PD modeling will likely be the focus of the upcoming R/Pharma conference.Keynotes
Robert Tibshirani , Profesor of Biomedical Data Science, and Statistics at Stanford University
Victoria Stodden (@victoriastodden), Associate Professor of Information Sciences at the University of Illinois at Urbana-Champaign
Michael Lawrence (@lawremi), Core Member of R and Bioconductor and Computational Biologist at Genentech
Location
The Omni Hotel 155 Temple Street New Haven, CT
Lodging and Dining
For lodging, click the following link to the Omni Hotel.
The conference will go from 7am to 5pm daily. Breakfast, lunch, and snacks will be provded on both days. There will be a reception on Friday from 5pm to 6:30 pm where food and drinks will be served.
The Omni Hotel does serve dinner in its rooftop restaurant. If you would like to venture out a little further the following restaurants are recommended.
| Restaurant | Address | Phone | Type of food |
|---|---|---|---|
| Olea | 39 High Street | 203-780-8925 | Spanish, vegetarian friendly |
| Zinc | 964 Chapel Street | 203-624-0507 | American, contemporary |
| Union League Cafe | 1032 Chapel Street | 203-562-4299 | French, contemporary |
| Barcelona | 155 Temple Street | 203-848-3000 | Mediterranean, European, Spanish |
| Claire's Corner Copia | 1000 Chapel Street | 203-562-3888 | American cafe, kosher, vegetarian, vegan friendly |
| Atticus Bookstore and Cafe | 1082 Chapel Street | 203-776-4040 | American |
| Prime 16 | 172 Temple Street | 203-782-1616 | American, pub |
| Louis' Lunch | 263 Crown Street | 203-562-5507 | American, the first hamburger |
| Shake Shack | 986 Chapel Street | 203-747-8483 | American, fast food |
| Mecha Noodle | 201 Crown Street | 203-691-9671 | Japanese, Vietnamese |
| Chipotle Mexican Grill | 900 Chapel Street | 203-785-0799 | Mexican |
| Starbucks | 1068 Chapel Street | 203-624-3361 | Coffee and tea |
| Frank Pepe Pizzeria Napoletana | 157 Wooster Street | 203-865-5762 | Pizza |
| Consiglio's | 165 Wooster Street | 203-865-4489 | Italian, vegetarian friendly |
Program
Friday
| Time | Speaker | Affiliation | Title |
|---|---|---|---|
| 7:00 - 8:00 | Breakfast | ||
| 8:00 - 10:00 | Mine Cetinkaya-Rundel | RStudio | Shiny Essentials |
| 10:00 - 10:30 | Break | ||
| 10:30 - 10:40 | Michael Kane | Yale University | Opening Remarks |
| 10:40 - 11:20 | Rob Tibshirani | Stanford University | How many units of platelets will the Stanford Hospital need tomorrow? |
| 11:20 - 11:40 | Nathaniel Phillips | Roche | FFTrees: How to create extremely simple, transparent, predictive decision algorithms for both machine learning and clinical decision applications |
| 11:40 - 12:00 | Peter Higgins | University of Michigan | Developing Random Forest Models for Medication Response and Implementation in the Epic EMR |
| 12:00 - 1:00 | Lunch | ||
| 1:00 - 1:20 | Max Kuhn | RStudio | tidymodels: a collection of opinionated modeling packages |
| 1:20 - 1:40 | Remi Besson | Ecole Polytechnique | Optimization of a Sequential Decision Making Problem for a Disease Diagnostic Application |
| 1:40 - 2:00 | Xinyue Li | Yale University | Visualizing and Analyzing Circadian Rythms of Infants via Activity Data |
| 2:00 - 2:20 | Steven Schwager and Jason Mezey | Medidata Solutions and Cornell University | Developing Analytical Software for Clinical Trials with R |
| 2:20 - 2:30 | Joseph Chou | Harvard University | Machine learning analysis of maternal pregnancy clinical notes to predict newborns at risk for neonatal abstinence syndrome |
| 2:30 - 3:00 | Break | ||
| 3:00 - 3:40 | Michael Lawrence | Genentech | Genomic Data Analysis with R and Bioconductor |
| 3:40 - 4:00 | Eran Bellin | Montefiore | How to Ask and Answer your Research Question using Electronic Data System data |
| 4:00 - 4:20 | Emily Zabor | Memorial Sloan Kettering Cancer Center | Teaching Survival Analysis to Clinical Collaborators |
| 4:20 - 4:30 | Peter Higgins | University of Michigan | From REDCap data to NIH Enrollment Tables |
| 4:30 - 4:40 | Stephan Kadauke | University of Pennsylvania | Teaching Reproducible Clinical Data Analysis to Medical Doctors |
| 5:00 - 6:30 | Reception |
Saturday
| Time | Speaker | Affiliation | Title |
|---|---|---|---|
| 7:00 - 8:00 | Breakfast | ||
| 8:00 - 10:00 | Tutorial | Ben Goodrich | An introduction to Bayesian inference in medicine using Stan |
| 10:00 - 10:30 | Break | ||
| 10:30 - 11:10 | Harlan Krumholz | Yale University | Dream Crazy: Imagine the Possibilities of Data Science in Medicine |
| 11:10 - 11:30 | Chris Kennedy | U.C. Berkeley | Varimpact: exploratory variable importance integrating causal inference and machine learning |
| 11:30 - 11:50 | Chinonyerem Madu | Children’s Hospital of Philadelphia | Using R to Automate the Investigation of Pediatric Health Disparities |
| 11:50 - 12:00 | Madeleine Gastonguay | Metrum Research Group | Development of an Open and General PBPK Model to Predict Maternal-Fetal Exposures for Drugs Metabolized by CYP Isoenzymes |
| 12:00 - 12:20 | Jacqueline Buros Novik | Icahn School of Medicine at Mount Sinai | Is It Working? Ongoing Evaluation of Drug Efficacy with Joint Models |
| 12:30 - 1:30 | Lunch | ||
| 1:30 - 1:50 | Jennifer Thompson | Vanderbilt University | The Life of a Reproducible Project in R |
| 1:50 - 2:10 | Denise Esserman | Yale University | Reproducible Clinical Trial Design for Patient Centered Outcomes Research (PCORI) |
| 2:10 - 2:30 | Keaven Anderson | Merck | Traceable and reproducible use of R for Analysis and Reporting under regulated environment |
| 2:30 - 3:00 | Break | ||
| 3:00 - 3:40 | Victoria Stodden | University of Illinois at Urbana-Champaign | Computational Reproducibility in Medical Research: Toward Open Code and Data |
| 3:40 - 4:00 | Elizabeth Claus | Yale University | Obstacles to Open Science: A Case Study with the Low-Grade Glioma Registry |
| 4:00 - 4:20 | Raymond Balise | The University of Miami | A Web App to Visualize Cancer Risk Factors for 900+ Neighborhoods in Florida - ShinyNeighborhood |
| 4:20 - 4:50 | Beth Atkinson, Joseph Chou, Peter Higgins, Stephan Kadauke, Chinonyerem Madu, and Jack Wasey | Roundtable Discussion: Bridging the Two Cultures | |
| 5:00 - | Drinks offsite |
Sponsors
If you are interested in sponsoring the conference, you may either contact us at r-medicine@protonmail.com or you can register as a sponsor using the Registration link. Sponsorship price is $5,000 and includes two tickets to the conference, a table at the conference furnished with 2 chairs and power setup in a location that will attract attended traffic, and your corporate logo listed on the conference website and conference program.
Committee
- Beth Atkinson, The Mayo Clinic
- Denise Esserman, Yale University (Program Chair)
- Michael Kane, Yale University (Conference Chair)
- Balasubramanian Narasimhan (Naras), Stanford University
- Joseph Rickert, RStudio
- Hongyu Zhao, Yale University
Contact
Questions, comments, and concerns may be directed to r-medicine@protonmail.com
R / Medicine is dedicated to providing a harassment-free conference experience for everyone regardless of gender, sexual orientation, disability or any feature that distinguishes human beings. For more information, please see the R Consortium code of conduct.