Principal Investigator: Dr Madeleine Cule
Calico Life Sciences LLC, South San Francisco, California, USATags: 44584, Computer Vision, Imaging, Liver, Machine Learning, Metabolism, MRI
Collaborator: Professor Jimmy Bell
Collaborator institution: University of Westminster, London, UK
Chronic metabolic, cardiovascular, and liver disease are amongst the greatest public health burdens, and there is a paucity of effective treatments. The UK Biobank imaging data provides a new window into the organs involved in these conditions (e.g. heart, liver, pancreas, spleen), as well as systemic changes. The aim of this project is to develop new machine learning methods to better understand the relationship between organ form (as visible on MRI or DEXA) and function. We propose to apply recent advances in artificial intelligence, techniques which have already transformed other fields, to better understand the changes that occur within specific organs, and how these relate to disease. These methods could be used to identify people at risk of disease, to identify genetic or lifestyle factors, or to inform the development of new treatments.