Interfacing is a project bringing together scientists and patients to discuss the current role of data in pancreatic cancer research.
Through a series of qualitative research questions participants created their own 'data self portraits' during a virtual art workshop. These self portraits were then photographed microscopically to create a dataset of 1000 images. This dataset was then used to train an AI model similar to those currently used by medical researchers to improve early diagnosis of pancreatic cancer.

This created a film of new, shifting, hybrid images that represent how the scale of datasets used in medical research unify the contributors as they become anonymized by the process, representing the disparity between the macrocosm of big data and the microcosm of personalised individual patient care. This film is a collaboration between artificial intelligence, artist, medical researchers, pancreatic cancer patients and their carers.

This project was made possible with funding from UCL & WEISS: Wellcome/EPSRC Centre for Interventional and Surgical Sciences.

This project was a collaboration between artist Molly Macleod, Senior Research Fellow at WEISS & UCL Ester Bonmati, Clinical Research Fellow at WEISS & UCL Alexander Ney, Professor of Hepatology & Gastroenterology at UCL Stephen Pereira, Postdoctoral Training Fellow at UCL Alexander Grimwood. This project was managed and overseen by Simon Watt & made possible with funding from UCL and WEISS: Wellcome/EPSRC Centre for Interventional and Surgical Sciences.