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Podcast Features Women Leaders at Intersection of Data Science and Genetics

Listen to women leaders across the data science profession, as they share their advice, career highlights, and lessons learned along the way. In season one, the Women in Data Science (WiDs) podcast takes a unique look into the lives of two women working at the intersection of data science and genetics:

  • Chiara Sabatti, professor of biomedical data science and of statistics at Stanford University, discusses trends in data science in genetics. Watch now
  •  Nilah Monnier Loannidis, a postdoc in the Department of Biomedical Data Science at Stanford University, discusses the role of data in her career and new ways to collect data. Watch now

This podcast is brought to you by the Stanford Institute for Computational & Mathematical Engineering (ICME) and the Stanford School of Engineering. Support for this podcast and other Women in Data Science initiatives has been provided by Intuit, Microsoft, SAP, Walmart Labs, and Western Digital. The Mobilize Center is one of the initial sponsors of the Women in Data Science Conference. To listen to all the WiDS episodes, click here.

“Our Voice” citizen-science project featured in 3M Particles website

Mobilize Center faculty member Dr. Abby King and her team’s “Our Voice” citizen-science project is featured in 3M’s Particles website. The project engages community members in improving their neighborhoods and making them more conducive for physical activity. Using a tablet-based app, people can take geo-coded photos and videos to highlight for policy makers and community leaders which neighborhood areas are in greatest need of improvement. This project is synergistic with Dr. King’s earlier study published in Nature with other Mobilize Center collaborators that analyzed data from 720,000 people and found a correlation between a location’s walkability and activity levels. Read more

The Mobilize Center Funds 6 Students to Attend This Year’s Machine Learning for Healthcare Conference

This year the Mobilize Center supported 6 students to attend The Machine Learning for Healthcare Conference (MLHC) at Stanford University on August 17-18, 2018.

Congratulations to Jeeheh Oh, Jacob Fauber, Bryan Lim, Xinyuan Zhang, Bryce Woodworth, and Zelun Luo! We welcome you to read their papers below:

Bryan Lim, Oxford University. Disease-Atlas: Navigating Disease Trajectories using Deep Learning

Bryce Woodworth, UC San Diego. Preference Learning in Assistive Robotics: Observational Repeated Inverse Reinforcement Learning

Jacob Fauber, UC Riverside. Modeling “Presentness” of Electronic Health Record Data to Improve Patent State Estimation

Jeeheh Oh, University of Michigan. Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks 

Xinyuan Zhang, Duke University. Multi-Label Learning from Medical Plain Text with Convolutional Residual Models

Zelun Luo, Stanford University (PI: Fei Fei). Computer Vision-based Descriptive Analytics of Seniors’ Daily Activities for Long-term Health Monitoring

Journal Article on Best Practices for Machine Learning in Human Movement Biomechanics

Our article “Machine Learning in Human Movement Biomechanics: Best Practices, Common Pitfalls, and New Opportunities” in the Journal of Biomechanics has just been published on-line.  In the article, we review published studies that apply machine learning to neuromuscular and musculoskeletal diseases, identify best practices and common pitfalls, and also provide recommendations for training and evaluating machine learning models. We hope the community finds this to be a useful guide for incorporating machine learning into biomechanics.

Workshop: Rapid Biomedical Knowledge Base Construction from Text

Do you want to automatically identify relationships mentioned within the scientific literature, e.g., which biomarkers are related to a particular disease? Do you want to analyze clinical notes to extract patient-reported functional capabilities related to a given treatment? 

Snorkel enables you to accomplish these tasks. It automatically extracts information from unstructured data sources, such as the scientific literature and clinical notes, without using large, labeled training datasets, which are often lacking in biomedicine. You can learn how to use the Snorkel platform in a hands-on workshop at Stanford University on November 6-7, 2018. On the first day, participants will learn about the Snorkel workflow through brief lectures and hands-on activities. On the second day, participants will utilize their new knowledge to apply Snorkel to a real-world problem using the scientific literature or electronic health record data. To attend, submit your application for consideration by Friday, September 21st, 2018. Learn more

Biomechanics and Machine Learning: Current Successes and New Opportunities

Apoorva Rajagopal from the Mobilize Center will be giving a talk on “Biomechanics and Machine Learning: Current Successes and New Opportunities” at the upcoming American Society of Biomechanics (ASB) Conference in Rochester, Minnesota at the Mayo Civic Center. The talk is part of the “Next Gen Sensors & Data Symposium” on the morning of August 9th (Thursday), 9:30 – 11:00am, in Ste 105. The symposium will open with a short intro talk by Bryan Conrad from Nike followed by 10-minute talks from each of five speakers, a moderated panel discussion, and an open discussion with the audience.

Trevor Hastie elected to the National Academy of Sciences

The Mobilize Center is delighted to announce that Mobilize Center faculty member Trevor Hastie was elected to the National Academy of Sciences. Dr. Hastie is an outstanding statistician, known for his work in applied regression and classification methodologies and more recently his efforts in data mining and prediction problems in biology and medicine. Within the Mobilize Center, he has worked with our trainees to demonstrate an association between physical activity and knee cartilage microstructure, predict the progression of movement disorders in children with cerebral palsy, and predict osteoarthritis progression. Please join us in congratulating Dr. Hastie for being a newly elected member of the National Academy of Science!

Seminar on Machine Learning Explainability

Dragutin Petkovic from the Computer Science Department at San Francisco State University presented “Toward Explainable Machine Learning – RFEX: Improving Random Forest Explainability” at last week’s Mobilize Center seminar. The abstract for the talk is below and the presentation slides are available here.
Abstract: Machine Learning (ML) methods are now influencing major decisions about patient care, new medical methods, drug development and their use and importance are rapidly increasing in all areas.  However, these ML methods are inherently complex and often difficult to understand and explain resulting in barriers to their adoption and validation. We define explainability in ML as easy to use information explaining why and how the ML approach made its decisions. We believe that much greater effort is needed to address the issue of ML explainability because of the ever increasing use and dependence on ML in many applications and the need for increased adoption by non-ML experts. 
In our talk, we will 1) summarize a workshop discussion on ML explainability organized jointly with Profs. L. Kobzik and C. Re at the 2018 Pacific Symposium on Biocomputing (PSB) and 2) describe our work on Random Forest Explainability (RFEX) (joint work with Prof. R. Altman, M. Wong and A. Vigil). RFEX provides easy-to-interpret explainability summary reports from trained RF classifiers to improve the explainability for users who are often non-experts. We tested RFEX with the FEATURE program to predict functional sites in 3-D molecules based on their electrochemical signatures (features). Through formal usability testing with expert and non-expert users, we found the RFEX explainability report significantly increased explainability and user confidence in RF classification.

Young investigators competition at ISMB 2018 -Deadline is April 5th, 2018

A competition for young investigators associated with the Big Data to Knowledge (BD2K) Initiative will be held in conjunction with the 26th Conference on Intelligent Systems for Molecular Biology (ISMB 2018). ISMB 2018 will be held on July 6-10 in Chicago, Illinois. The conference is sponsored by the International Society for Computational Biology.

ISMB 2018 is expected to include several sessions featuring talks from officials of the National Institutes of Health on biomedical data science, projects under the Big Data-to-Knowledge (BD2K) Initiative and training programs. The conference brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems.

As part of BD2K, there will be a competition for Young Investigators. 6 individuals will be selected for oral presentation and travel awards, including ISMB registration and $500 towards your travel support to ISMB 2018. These individuals will be invited to give talks during a special NIH BD2K session at ISMB, and the abstracts will be recognized at the ISMB award ceremony.

To be considered for this award:

• Submit an abstract to ISMB 2018 here:
• Send a copy (PDF version) of this abstract and submission to by April 5th, 2018 deadline. When submitting, please include (1) your affiliated BD2K project when you submit this to us, including BD2K grant number, and (2) a letter of support from the project PI or training director. (If you are the project PI, no need for this letter).
• Awardees will be informed by May 1st, 2018.

Eligibility: to qualify for this award, a Young Investigator is any individual who is (1) an existing graduate student, or (2) a postdoctoral fellow in a BD2K-funded laboratory/program; or (3) any individuals who are considered an NIH Early Stage Investigator (ESI) and have received funding support from an NIH BD2K Award (the ESI does not have to be a PI on the NIH award). Two or more finalists will be selected from each of these three categories.

There will also be a networking event for Young Investigators at the evening of Sunday July 8th, 2018, with more details to follow. If you are interested in participating in this event, please email:

Outstanding Paper Award for Surgical Science from the Spine Journal

Mobilize Center faculty Matthew Smuck and colleagues won the 2017 “Outstanding Paper: Surgical Science” at the North American Spine Association (NASS) 32nd Annual Meeting for their paper“Objective Measurement of Function following Lumbar Spinal Stenosis Decompression Reveals Improved Functional Capacity with Stagnant Real-Life Physical Activity” in The Spine Journal. Results showed improvements in self-reported function and objectively measured physical capacity 6 months post-surgery, but not in physical performance as measured by continuous activity monitoring. Read more.