Challenge: Can you identify a human health problem that might be resolved with big data and a computational solution? Are you working on a problem that could benefit from new algorithmic solutions or improvements? Are you aware of a dataset that could be used to solve this problem or generate further ideas for solutions?
The problem must fall into the clinical and translational research realm. Topics covered might include diagnostics, therapeutics, public health, technology, or outcomes.
- Applying human genomic data to solve a scientific challenge
- Using epidemiologic or other data to address a public health issue
- Using image analysis to resolve a diagnostic or therapeutic issue
- Using data available on a government website to resolve a new question
Eligibility: Open to the public
Multiple prizes between $500 and $1500 will be awarded, up to $10,000 in total.
Application Due: On or before July 15, 2017
Note: You will not be asked to submit a dataset. You will be asked only to briefly define (in three pages or less) a problem that could benefit from a computational answer and characterize the data. In characterizing the data, consider how it might be used for a future ideation challenge related to your question topic. Data can be from your own research or from other private or public sources. This crowd sourcing opportunity is intended to help identify new opportunities as well as difficult "bottleneck" problems that create significant roadblocks to progress in healthcare, translational science, and technological innovation.
The goal of generating these submissions is to provide a basis for developing opportunities that will continue to address important questions through cross-CTSA or local challenges in the near future.
Sponsored and administered by Harvard Catalyst and the Crowd Innovation Laboratory at Harvard Business School. Additional funding is provided by the Laura and John Arnold Foundation.