​Oncology data holds enormous promise for AI, but only if teams can tell when a dataset is actually fit for the question being asked, and can explain why.

​Join The Open Accelerator, OncoSys AI, and Northeastern for a four-day hackathon to build practical tools that make oncology data safer, clearer, and more useful for responsible AI.

​Schedule

• ​Wednesday, November 11: Virtual kickoff

• ​Thursday–Friday, November 12–13: Virtual Build days

• ​Saturday, November 14, 10:00 AM–5:00 PM: In-person finals at the Cabral Center, Northeastern University, Boston

​Challenge tracks
Track 1: Cohort Firewall

• ​Build a tool that decides whether an oncology dataset is ready for a proposed AI question. It returns one of four verdicts: Ready, Conditional, Blocked, or Insufficient Evidence.

​Track 2: Evidence Navigator

• ​Turn complex oncology data-readiness findings into clear evidence, side-by-side comparisons, and concrete next actions.

​ Before you register

• ​Team size: 3–5

• ​Bring a working prototype to finals. Slides alone won’t do it.

• ​Use only synthetic, openly licensed, or event-approved non-sensitive data

• ​No patient data, and no tools that make clinical decisions

​Who should join
Developers, data scientists, designers, researchers, and anyone working where healthcare meets AI. Cohort Firewall suits builders who like rules, logic, and data. Evidence Navigator suits people who can make complex findings easy to understand.

​Organized by

• ​Northeastern University · OncoSys AI · The Open Accelerator · Red Hat