New AI tool could cut wasted efforts to transplant organs by 60%

"Doctors have developed an AI tool that could reduce wasted efforts to transplant organs by 60%. Thousands of patients worldwide are waiting for a potentially life-saving donor, and more candidates are stuck on waiting lists than there are available organs."

"Now doctors, scientists and researchers at Stanford University have developed a machine learning model that predicts whether a donor is likely to die within the timeframe during which their organs are viable for transplantation. The AI tool outperformed the judgment of top surgeons and reduced the rate of futile procurements which occur when transplant preparations have begun but the donor dies too late by 60%."

"By identifying when an organ is likely to be useful before any preparations for surgery have started, this model could make the transplant process more efficient, said Dr Kazunari Sasaki, a clinical professor of abdominal transplantation and senior author on the study. It also has the potential to allow more candidates who need an organ transplant to receive one."

Thousands of patients worldwide wait for life-saving donor organs while demand exceeds supply. Donation after circulatory death (DCD) has expanded liver transplant access by using donors who die after cardiac arrest, but about half of DCD cases are cancelled because donors often do not die within the 45-minute window needed to preserve organ quality. Surgeons commonly reject livers when death occurs too late due to increased recipient complication risk. A machine learning model developed at Stanford predicts whether donors will die within the viable timeframe, outperforming top surgeons and reducing futile procurements by 60%. By identifying usable organs before surgical preparations begin, the model can reduce financial and operational strain on transplant centers and increase transplant access.

Read at www.theguardian.com