Leeds students lead overnight sprint to explore AI in healthcare

Students and technology professionals built 19 health-focused products overnight at HELIX 2026, a student-led hackathon hosted at the University of Leeds.

Held on 24 and 25 October, the Leeds AI Society event brought together 60 participants for an intensive sprint exploring how artificial intelligence and other technologies could be applied to healthcare.

More than 100 people applied to take part. Those selected included University of Leeds students and technology professionals, with backgrounds spanning computer science, medicine, biochemistry, biology and other healthcare-related disciplines.

Computer Science student Kirsten Tan, who led and hosted HELIX, worked with the Society’s organising committee to develop the event. Two weeks before the competition, it had been planned as an eight-hour, one-day event without confirmed sponsors; going into the weekend, after incredibly hard work, the organisers secured a prize fund, talks and workshops, assembled four judges, and expanded the programme into an overnight format.

Teams were given an open brief, allowing them to pursue any healthcare idea using any technology rather than responding to a set of predefined challenges.

Shilpi Sinha, a Senior Business Analyst at NHS England who helped judge HELIX 2026, said: “By keeping the brief open to any idea and any technology, it gave them the freedom to challenge conventional thinking, explore possibilities and build solutions without being limited by how things are currently done in the industry. That freedom to experiment is often where the most exciting innovations begin!”

Building through the night

Participants worked in teams to develop an idea into an early-stage product, then presented it to the judging panel. Some also moved beyond software to incorporate hardware prototypes.

The interdisciplinary format encouraged participants with healthcare knowledge to work alongside those with technical expertise. Participants created each of the 19 projects during the overnight sprint and assessed them as hackathon prototypes rather than clinically ready technologies.

Kirsten said: “Watching the hackers work through the night to bring their ideas to life was genuinely inspiring. Giving up a whole weekend to tackle real healthcare problems takes commitment, and I’m so proud of everyone who came. Every single team submitted a project and presented it, which says a lot about the energy in the room.

“This is just the start. We’re already planning more events where people can build, learn and show off what they can do!”

Winning projects

First place (sponsored by the School of Computer Science): SpyMotion

Lucia Regoroni, Emanuele Magaroni, Ivy Zhang and Amir Zheng

HELIX 2026 1st Place SpyMotion team posing for a photo in front of a projection screen

SpyMotion is a privacy-focused rehabilitation platform that supports people recovering from spinal cord injuries. Using computer vision, it lets users track changes in their movement with a phone camera, assess wheelchair accessibility from images, and manage medication reminders, helping them gain greater independence between healthcare appointments.

Learn more about SpyMotion at DevPost.

Second place (sponsored by the UKRI Centre for Doctoral Training in AI for Medical Diagnosis and Care): Nova

Lee Jun Siong, Ruolin Wang, Adam Sweidan and Mohammed Almahri

HELIX 2026 2nd Place Nova team standing in front of a projector and posing for a photo

Nova is an AI-powered platform designed to streamline hospital systems and reduce clinicians’ administrative workload. It uses conversations and patient history to help produce clinical notes, with multilingual and multi-session support for appointments. Its locally run AI approach also aims to keep sensitive patient information secure.

Read the DevPost page for Nova.

LIDA Award for Most Responsible Use of Data: Her Health

Jinesh Dugar, Hareem Ghouri, Jeffrey Chan and Salma Bushra Islam

HELIX 2026 LIDA Award (Most Responsible Use of Data) Her Health team standing in front of a projector

HerHealth is a privacy-focused women’s health platform designed to help users track symptoms, identify unusual patterns and communicate their experiences more clearly with healthcare professionals. Combining symptom tracking, NHS and NICE guidance and AI-supported tools, it can highlight potential concerns and create concise summaries to support conversations with GPs.

Learn more about Her Health at DevPost.

The projects were assessed by Owen Johnson, Associate Professor at Leeds and Co-Director of the Leeds UKRI Centre for Doctoral Training in AI for Medical Diagnosis and Care; John Bowman, Head of AI Enablement at PokerStars and founder of AISAT.UK; Shilpi Sinha; and Leeds Computer Science student Robert Vassallo.

The event was supported by the School of Computer Science, the UKRI Centre for Doctoral Training in AI for Medical Diagnosis and Care and Leeds Institute for Data Analytics. OpenAI, Digital Education at Leeds and AISAT also contributed to the programme.