Could AI improve the organ transplant process?

It is hoped the new study will eventually lead to a welcome increase in the number of organs available for transplant.

Currently, surgeons examine donor organs and use their own judgement to assess whether they are of good enough quality to be suitable for transplanting into patients.

This new method uses AI and its ability to recall tens of thousands of images of donor organs to identify those that offer the best chance of transplant success.

The team of experts behind the research, known as OrQA - Organ Quality Assessment - claim it could result in up to 200 more patients receiving kidney transplants and 100 more receiving liver transplants every year in the UK.

While work is ongoing to define the technology, the team, which includes experts from the University of Oxford, believes it will deliver future healthcare results in the UK.

Professor Hassan Ugail, Director of the Centre for Visual Computing at the University of Bradford, whose team is designing the image analysis, said:

"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.

"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.

"This will ultimately mean a surgeon could take a photo of the donated organ, upload it to OrQA and get an immediate answer as to how best to use the donated organ."

A key part of the OrQA assessment will be to look for damage, pre-existing conditions, and how well blood has been flushed out of the organ.

Related: Call for cloud-based regulatory assessments