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The new system completed an analysis of brain scan images from 130 people, where the newly developed algorithm operated with nearly 100 accuracy. It also proved to be more accurate, sensitive and specific than any other existing method. The new method can identify signs of mild cognitive impairment (MCI) which is the step that follows from cognitive decline, and the step the comes before Alzheimer’s.
This method will prove important as often, MCI goes undiagnosed as it can be symptomless.
MCI will not always necessarily develop into Alzheimer’s, but it is definitely a very important indicator that someone who has signs of MCI may develop Alzheimer’s in the future.
MRI scans can be done manually by humans, but deep learning techniques have proved a much faster and more accurate and reliable method.
Deep learning techniques take massive databases of training data, and can apply that knowledge to data in novel ways.
Rytis Maskeliūnas, an informatics professor from the Kaunas University of Technology (KTU) in Lithuania, said: “Modern signal processing allows delegating the image processing to the machine, which can complete it faster and accurately enough.
“Of course, we don’t dare to suggest that a medical professional should ever rely on any algorithm 100 percent.
“Think of a machine as a robot capable of doing the most tedious task of sorting the data and searching for features.”
Specialists work with the AI by confirming potential cases that the computer software has identified.
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“Obviously, such high numbers are not indicators of true real-life performance, but we’re working with medical institutions to get more data.
“Medical professionals all over the world attempt to raise awareness of an early Alzheimer’s diagnosis, which provides the affected with a better chance of benefiting from treatment.”
Alzheimer’s disease is the most common cause of dementia and is responsible for 70 percent of cases globally.
Right now, there are around 850,000 people with dementia in the UK. This is projected to rise to 1.6 million by 2040 due to an ageing population.
The study was published in the journal Diagnostics.
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