Fujifilm and the National Center of Neurology and Psychiatry (NCNP) have just released new research which shows that AI technology could help to predict whether or not someone is likely to get Alzheimer's disease. By monitoring brain activity, Fujifilm and NCNP say that they are able to predict whether a patient with mild cognitive impairment (MCI) will progress to having dementia within two years with an accuracy of up to 88%.
Alzheimer's disease is the most common cause of dementia and it is estimated that 55 million people worldwide have the neurological condition that causes loss of memory. As the population ages, it’s expected that by 2050, more than 139 million people will suffer from the life-changing condition.
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Using advanced image recognition technology, Fujifilm and NCNP have developed a way in which they are able to monitor the progression of Alzheimer's (opens in new tab) from three-dimensional MRI scans of the brain. Deep learning AI technology monitors the hippocampus and the anterior temporal lobe, two areas highly associated with the progression of Alzheimer's and detects fine atrophy patterns associated with Alzheimer's.
Atrophy is the progressive degeneration or shrinking of muscle or nerve tissues and in relation to dementia, it takes place in the brain. Two types of common atrophy’s are found in patients with MS - muscle atrophy which causes certain muscles to waste away and cerebral atrophy which is a loss of neurons and connections between neurons.
The research shows that when AI technology learns an entire brain, it focuses not just on the two areas usually associated with Alzheimer's but also on the cerebrospinal fluid (a clear colorless fluid found in your brain and spinal cord) and the occipital lobe which is the visual processing area of the brain.
By learning to differentiate between areas of the brain that are less relevant to Alzheimer's, it is much more likely that a highly accurate prediction can be made about the progression of mild cognitive impairment.
While this technology cant be used to diagnose, prevent or treat dementia, it is hoped that further clinical trials will verify the usefulness of this technology. If the algorithm used to monitor the progression of dementia can also be used to monitor the progression of other mental and neurological disorders, it could help with prognosis and treatment responsiveness.
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