British scientists announced [June 20] that they have developed a machine-learning algorithm that can determine, with 98% accuracy, whether Alzheimer’s disease is present in a patient by looking at a single brain scan.
“Waiting for a diagnosis can be a horrible experience for patients and their families. If we could cut down the amount of time they have to wait, make diagnosis a simpler process, and reduce some of the uncertainty, that would help a great deal,” said Eric Aboagye, a professor of cancer pharmacology at Imperial College London and the study’s lead researcher, in a press release.
The novelty of Aboagye’s team’s approach lies in adapting methods that were developed to classify cancer tumors to MRI scans of more than 400 patients with Alzheimer’s both early-onset and late-stage, healthy brains and also patients with Parkinson’s and other neurological conditions.
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The team “trained” the algorithm using these scans as inputs, teaching it the difference between regions and features that indicate Alzheimer’s disease and features that do not point to the presence of Alzheimer’s. By teaching it to tell signs from Alzheimer’s disease from red herrings, the algorithm became capable of making predictions when it was presented with new data.
