Methodologies: Machine Learning, dynamic programming, data analytics, statistics, Markov decision processes
Application: The utilization of ineligible donor organs, Marginal kidney transplants
Organ transplants have been instrumental in preserving countless lives. However, the significant demand for organs, when met with their limited supply, often results in extended waiting periods for those in need. While an eligible organ transplant would be ideal in most cases, the urgency created by factors such as prolonged waiting times and the rapid progression of diseases often makes the use of marginal organs a more viable option.
We hope to better understand the utilization of ineligible donor organs in order to reduce their discard rate.
We aim to refine decision-making processes with a focus on kidney transplants. It aims to prioritize patients for whom transplantation would result in the maximal benefit for the entire population, while ensuring fairness across all genders and races, particularly when dealing with marginal kidneys.