Approximately 24 million people are affected by Alzheimer’s worldwide and that number is expected to double due to the ageing population.
ADVERTISEMENTResearchers in Lithuania have developed a deep learning-based method that can predict the possible onset of Alzheimer’s disease with over 99 per cent accuracy.
The method uses Artificial Intelligence and Deep Learning to analyse brain images. It is faster than manual analysis, which also requires specific knowledge of the changes associated with Alzheimer’s.
Researchers from Kaunas University of Technology (KTU) in Lithuania developed the method while analysing functional MRI images obtained from 138 subjects. They found it performed better in terms of accuracy, sensitivity and specificity than previously developed methods.
The findings of the research were published in the journal Diagnostics' on Monday.
The method could be a game-changer in how Alzheimer’s and dementia are detected as according to the World Health Organization (WHO), Alzheimer’s is the most frequent cause of dementia and contributes up to 70 per cent of dementia cases.
Technologies can make medicine more accessible and cheaper. Although they will never (or at least not soon) truly replace the medical professional,Rytis Maskeliūnas, a researcher at the Department of Multimedia Engineering at KTU.
Approximately 24 million people are affected by Alzheimer’s worldwide and that number is expected to double due to the ageing population.
One of the first signs of Alzheimer’s is mild cognitive impairment (MCI), an early stage of memory loss or other cognitive ability loss. The earliest stages often have almost no clear symptoms but can be detected by neuroimaging.
**Why is early detection important? **
“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,” said Rytis Maskeliūnas, a researcher at the Department of Multimedia Engineering at KTU.
He said although it was not the first attempt to diagnose the early onset of Alzheimer's from similar data, the main breakthrough was the accuracy of the algorithm.
“Obviously, such high numbers are not indicators of true real-life performance, but we're working with medical institutions to get more data," he said.
"We need to make the most of data. That's why our research group focuses on the European open science principle, so anyone can use our knowledge and develop it further. I believe that this principle contributes greatly to societal advancement."
Replacing medical professionals?
The chief researcher said the algorithm could be developed into software, which could analyse data from those more prone to Alzheimer's, for example, those over the age of 65 or who have high blood pressure.
Although the technology could help medical professionals with Alzheimer’s diagnoses, Maskeliunas warned it cannot replace them.
"Technologies can make medicine more accessible and cheaper. Although they will never (or at least not soon) truly replace the medical professional, technologies can encourage seeking timely diagnosis and help," he said.
