Teams of students spend a weekend building AI solutions to real healthcare problems. The brief is open: any healthcare problem, any idea, any tech. We just want to see what you can build when clinical insight meets AI.

Hosted by the Leeds AI Society.

Schedule

Saturday 24 October

09:00 Registration starts
09:30 Team formation
10:00 Opening ceremony
10:30 Build starts
10:30 Healthcare talk: Clinical Challenges in Surgery with Mikolaj Kowal
11:00 OpenAI workshop: From Prompt to Prototype
12:30 Lunch
21:30 Evening checkpoint: time check, submission and overnight info
21:35 Evening activity: quiz or board games
00:00 Overnight hacking

Sunday 25 October

08:00 Breakfast
10:30 Countdown begins, with warnings at 1 hour, 30, 15 and 5 minutes
11:30 Devpost deadline, followed by lunch and a break
12:30 Final pitches: 4 minutes of presentation and demo, plus 2 minutes of Q&A per team
14:00 Judges deliberate
14:20 Closing ceremony and awards

Thanks to our sponsors

School of Computer Science · CDT · LIDA · Digital Education · OpenAI · AI SAT

Requirements

Data rules: read this one

Do not use real patient data. No exceptions.

Not anonymised extracts, not a screenshot from a placement, not a dataset a friend “can get hold of”. Use synthetic or openly licensed public data only. See the Resources tab for a list.

Any submission containing identifiable patient information will be disqualified and deleted. This protects you more than it protects us.

Required submission details

Project name and short tagline. One line: what it does, not what it’s called.
Description. Cover four things:
- The problem. Who has it, and how do you know it’s real?
- Your solution. What did you build?
- How you built it. Stack, architecture, anything you’re proud of.
- What’s next. What would you do with another week?
Built-with tags. List your languages, frameworks, APIs and datasets.
Team members. Add every member to the submission. If someone isn’t on the submission, they aren’t on the project, and that matters for prizes.
Submission questions. When you submit, you’ll be asked for:
- Your team name
- What data you used and how you considered privacy, consent and bias. This is used to judge the Most Responsible Use of Data award.
- What you built during the hackathon and what was pre-existing code, templates or APIs
- A link to your code repository. GitHub, GitLab, anything judges can open without an account.

Hackathon Sponsors

Prizes

£800 in prizes

Overall First Place - sponsored by the School of Computer Science

£300 in cash

1 winner

Overall Runner Up - sponsored by the UKRI Centres for Doctoral Training

£200 in cash

1 winner

Most Responsible Use of Data - sponsored by the Leeds Institute for Data Analytics

£300 in cash

1 winner

Judges

Owen Johnson
Associate Professor @ University of Leeds

John Bowman
Head of AI Enablement @ Pokerstars

Shilpi Sinha
Senior Business Analyst @ NHS England

Judging Criteria

Creativity & Innovation
How original is the idea? Projects that tackle a healthcare problem in a fresh way or apply AI somewhere new will score highest.
Technical Sophistication
How well is it built, and how much actually works? A smaller project that runs reliably beats an ambitious one that doesn’t.
Impact
How much difference could it make to patients, clinicians or the NHS? Show you understand the clinical context and how it could be used in practice.
Design & User Experience
Is it clear, accessible and suited to its real users, whether patients or busy clinicians? Fit to the user matters more than polish.
Most Responsible Use of Data
Is the data appropriate, and have privacy, consent and bias been considered? Explain your choices in the data question on your submission.

University of Leeds - Helix	Public
£800 in cash	35 participants