Artificial intelligence could spot early signs of Alzheimer’s disease more than six years before a patient would normally be diagnosed, research suggests.
Scientists conducting a small pilot study trained a self-learning computer programme to recognise features in brain scans which are too subtle for humans to see.
The system was able to detect the beginnings of Alzheimer’s in 40 patients an average of more than six years before they were formally diagnosed.
The American researchers trained the “deep learning algorithm” using more than 2,100 PET (positron emission tomography) scans from 1,002 patients.
PET scans measure metabolic activity in the brain by tracking the uptake of a radioactive glucose compound injected into the blood.
Research has linked the development of Alzheimer’s to changes in metabolism in certain parts of the brain, but these can be difficult to spot.
After assessing thousands of scans, the machine was able to learn how to recognise patterns indicated disease.
As a test, the algorithm was given a set of 40 scans from 40 patients it had never studied before. It proved to be 100% accurate at detecting Alzheimer’s disease an average of more than six years prior to a patient’s final diagnosis.
Dr Jae Ho Sohn, a member of the team from the University of California at San Francisco, said: “We were very pleased with the algorithm’s performance. It was able to predict every single case that advanced to Alzheimer’s disease.”