Is natural language processing useful in predicting organ acceptance?
UNOS data scientists explore donor admission text to help understand and predict how kidney acceptance decisions are made
UNOS data scientists explore donor admission text to help understand and predict how kidney acceptance decisions are made
Research shows family patterns affecting risk can predict whether a living donor will develop end-stage renal disease decades after donating a kidney to a related recipient.
Through focused quality improvement and education practices, LifeLink of Georgia has almost tripled recovery of African-American donors.
71 percent of organ procurement organizations increased organ donations in 2018, thanks to the generosity of donors and donor families.
Lung perfusion has more than tripled since 2015, growing from 1.7 percent to 6.3 percent and potentially expanding the pool of organs available for transplant.
More pediatric patients will receive transplants as a result of new OPTN liver distribution policy