IT'S A MATCH

HOW AI CAN IMPROVE THE SCIENCE OF ORGAN DONATION

- DAMIEN MARTIN

As far as the science of organ transplantation has come, rejections do still occur. Overall, rejection happens 10-15% of the time, though this varies by organ. There are various reasons this can occur, and often the trouble takes place before any operation. As good as doctors are, they sometimes select organs that are not right for the particular patient, or not suitable for transplantation at all. With its superior ability to sift through a lot of data, recognize patterns, and make predictions based off that information, AI might be able to help. It could select organs for transplantation much more accurately than humans ever could.

QUALITY ASSESSMENT

The UK's National Institute for Health and Care Research is putting more than £1 million ($1.22 million) toward the development of an Al-based recognition software called Organ Quality Assessment (OrQA) that uses a database of tens of thousands of images of organs to determine whether donor ones will be suited for transplantation. That's usually a job for surgeons, but it's one that a trained Al can do a lot better.

“Currently, when an organ becomes available, it is assessed by a surgical team by sight, which means, occasionally, organs will be deemed not suitable for transplant,” Professor Hassan Ugail, Director of the Centre for Visual Computing at the University of Bradford, said. “We are developing a deep machine learning algorithm which will be trained using thousands of images of human organs to assess images of donor organs more effectively than what the human eye can see.