Artificial Intelligence (AI) technology has the potential to facilitate surgical decision making
Our initial project is to train an AI algorithm to quantitatively and reproducibly evaluate steatosis and other features of donor biopsies to assess their impact on transplantation.
Specifically, we aim to 1) test the ability of AI models to determine the degree of steatosis; 2) recalibrate the association of steatosis with post-transplantation outcomes, and 3) to train AI to identify additional features of biopsies associated with post-transplantation outcomes.
Models will be tested on additional slides and compared to the pathologists’ labeling. Scoring by the AI model will be correlated with early post-liver transplantation outcomes to build a predictive model of the impact of steatosis on outcomes. We hope that these results will be to enable identification of livers suitable for transplant and reduce wrongly discard grafts. Subsequently, we will use this AI infrastructure to address other surgical challenges.