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Scientists create new technology to spot early Alzheimer’s with ’99 per cent accuracy rate’


ALZHEIMER’S can be predicted “with nearly 100 per cent accuracy” in an exciting artificial intelligence-led medical breakthrough, say researchers.

Experts in Lithuania have developed an algorithm which whizzes through the “most tedious task of sorting the data and searching for features” to help predict possible sufferers of the brain disorder.

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Alzheimer’s is the most common form of dementia,[/caption]

Researchers from the Kaunas University of Technology (KTU) have developed a “deep learning-based” method in aid of patients with the disease, which slowly destroys memory and thinking skills.

This method can “predict the possible onset of Alzheimer’s disease from brain images with an accuracy of over 99 per cent”, they said.

It was developed while analysing MRI images of the brains of 138 research participants.

They were trying to tackle the problem of manually analysing ‘functional’ MRI images – which measures brain activity by detecting changes associated with blood flow.

Trying to identify changes in the brain associated with Alzheimer’s not only requires specific knowledge but is also time-consuming.

But, applying ‘Deep learning’ and other Artificial Intelligence methods can speed this up by a significant timeframe, the experts said.

Deep learning is where massive amounts of data are analysed.

“Of course, we don’t dare to suggest that a medical professional should ever rely on any algorithm one hundred per cent.

“Think of a machine as a robot capable of doing the most tedious task of sorting the data and searching for features,” explained Rytis Maskeliunas, a researcher at the Department of Multimedia Engineering.

Maskeliunas added: “After the computer algorithm selects potentially affected cases, the specialist can look into them more closely, and at the end, everybody benefits as the diagnosis and the treatment reaches the patient much faster.

“We’re working with medical institutions to get more data.”

He said that the algorithm could be developed into software, which would analyse the collected data from vulnerable groups – those over 65, people with a history of brain injury, high blood pressure, etc.

One of the possible Alzheimer’s first signs is mild cognitive impairment (MCI) which is the stage between the expected cognitive decline of normal ageing and dementia.

The earliest stages of MCI often have almost no clear symptoms, but in quite a few cases can be detected by neuroimaging.

Doctors would be told about any anomalies detected, related to the early onset of Alzheimer’s.

Maskeliunas, the chief researcher, said the model could also be integrated and used to analyse different parameters, for example, monitoring eye movements’ tracking, face reading, or voice analysing.

“Technologies can make medicine more accessible and cheaper.

“Although they will never truly replace the medical professional, technologies can encourage seeking timely diagnosis and help,” added Maskeliunas.

According to the World Health Organisation, Alzheimer’s disease is the most frequent cause of dementia, contributing to up to 70 per cent of dementia cases.

Worldwide, some 24million people are affected, and this number is expected to double every 20 years.

Owing to societal ageing, the disease will become a costly public health burden in the years to come.

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The brain disease slowly wipes the memory over several years[/caption]

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