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Brits say computer better than docs at diagnosing Alzheimer’s

Computers are able to diagnose Alzheimer’s disease faster and more accurately than experts, according to research published in the journal Brain. The findings may help ensure that patients are diagnosed earlier, increasing treatment options.

Researchers from University College London found computer scans able to identify brain damage caused by Alzheimer’s with an accuracy as high as 96%. As a result, they said, it may be possible to diagnose patients earlier, increasing their chances of receiving effective treatment, possibly slowing the disease’s progression.

“The advantage of using computers is that they prove cheaper, faster and more accurate than the current method of diagnosis,” said Professor Richard Frackowiak of the Wellcome Trust Centre for Neuroimaging at the college. “The new method makes an objective diagnosis without the need for human intervention.”

Frackowiak added: “This [finding] will be particularly attractive for areas of the world where there is a shortage of trained clinicians and when a standardised reliable diagnosis is needed, for example in drug trials.”

The new method, developed by the University College London team, works by teaching a standard computer the differences between brain scans from patients with proven Alzheimer’s disease and people with no signs of the disease at all. The two conditions can be distinguished with a high degree of accuracy on a single clinical MRI scan.

This process could be especially useful for medical centres where facilities for extensive diagnostic workup are not available. One use, the researchers noted, might be to reassure healthy but worried elderly with mild memory problems that they are not suffering from early Alzheimer’s.

“The next step is to see whether we can use the technique to reliably track progression of the disease in a patient,” said Frackowiak. “This could prove a powerful and non-invasive tool for screening the efficacy of new drug treatments speedily, without a need for large costly clinical trials.”

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