Data Studio

The Data Studio is a collaboration between Spectrum (The Stanford Center for Clinical and Translational Research and Education) and the Department of Biomedical Data Science (DBDS). Its fundamental goal is to foster dialog between statisticians/data scientists and researchers in clinics and laboratories in order to drive excellence in health care research at Stanford. Data Studio is open to the Stanford community, and we expect it to have educational value for students and postdocs interested in biomedical data science.

Most sessions are an extensive and in-depth consultation for a Medical School researcher based on research questions, data, statistical models, and other material prepared by the researcher with the aid of our facilitator. During the Data Studio, the researcher explains the project, goals, and needs. Experts in the area across campus will be invited and contribute to the brainstorming. After the meeting, the facilitator will follow up, helping with immediate action items and summary of the discussion. Ultimately, we strive to pair up each PI with a data scientist for long term collaboration.

The last session of each month is devoted to drop-in consulting. DBDS faculty are available to provide assistance with your research questions. Bring any data, prior analyses, or other materials that you have. No advance notification is required, but you will reserve your place in the queue and help us prepare if you send a brief description of your project to Laurel Stell.

A Data Studio session may also be an informal, interactive presentation by a data scientist on a topic, such as advanced data visualization in R, the statistical properties of convolutional neural networks (CNN), etc. Previous mini-courses are archived here.

Interested in discussing your study in a Data Studio?

If you are a Medical School investigator, clinical or laboratory, who is interested in participating in one of the in-depth consultations, please fill in the consultation request form.

Schedule

The Data Studio is held each Wednesday 1:30-2:50pm during fall, winter, and spring quarters. Students may register for BIODS 232, but all are welcome to attend.

Currently scheduled topics are listed below, followed by links to topics and summaries from previous quarters. Click here to sign up for our mailing list. 

DATE
INVESTIGATOR
PROJECT TITLE
9/26
Drop-in consulting
10/3
Balasubramanian Narasimhan (Biomedical Data Science) and Neal Birkett (Cancer Clinical Trials Office)
Automatic generation of clinical trial reports
(Summary and resources)
10/10
Kari Nadeau (Medicine & Pediatrics)
Adaptive clinical trial design for milk allergy trial
(Summary and background reading)
10/17
MSOB X399
Jorg Goronzy & Chulwoo Kim (Immunology and Rheumatology)
Estimating the number of distinct clones in immune cell population
(Summary and background reading)
10/24
MSOB X399
Elizabeth Mellins (Pediatrics) & Guangbo Chen (Immunity Transplant Infection)
How to identify risk factors using an external control group? A case study of sJIA-ILD cohort
(Summary and background reading)
10/31
MSOB X399
Drop-in consulting
11/7
MSOB X399
Bruce Ling (Surgery)
Analytical challenges: multi-site multi-omics data production for population health
(Summary)
11/14
MSOB X399
Larry Chu, Dominick Zheng & Urvi Gupta (Anesthesiology, Perioperative and Pain Medicine)
Machine learning approach to screen for breast cancer with thermography
(Summary and background reading)
11/21
 
Thanksgiving break
11/28
Drop-in consulting
12/5
Chun-houh Chen, Research Fellow (Professor) and Director, Institute of Statistical Science, Academia Sinica, Taiwan
Research in Taiwan on health care data