Artificial Intelligence may allow early diagnosis of Alzheimer’s
An Artificial Intelligence technique developed by a team of scientists in Spain has the potential to be used for early diagnosis of Alzheimer’s by revealing brain patterns associated with the disease.
“The study uses deep learning techniques to calculate brain function predictors and magnetic resonance imaging to prevent Alzheimer’s disease. To do this, we have used different neural networks with which to model each region of the brain to combine them afterwards,” said researchers from the University of Malaga and the University of Granada, who worked jointly on the project.
This Artificial Intelligence (AI) technique aims to model high-level data abstractions in order to enable computers to differentiate the brain of a healthy person from that of an ill person, by automatically extracting the affected regions of interest, said the research published recently in the renowned International Journal Of Neural Systems.
Alzheimer’s disease, which currently affects more than 40 million people, is the most common neurodegenerative disease in elder people. Early diagnosis is crucial both to treat the disease and to help the development of new medicines, as it hasn’t been possible to find a cure so far.
The development of Alzheimer’s has been proven to be closely linked to structural changes -related to the gray matter, responsible for processing information- and functional ones -related to the white matter, which connects the different regions of the brain through fibers- in the brain connectivity network, since a significant loss of fibers also causes functional alternations, such as memory loss.
However, diagnosis remains a challenge in spite of the scientific advances made.
In this regard, computer aided diagnosis (CAD) is an important tool since it helps physicians to understand multimedia content obtained in tests carried out in patients, which allows a simpler and more effective application of the treatment.
The new techniques developed may also serve as a starting point for the improvement of accuracy in the diagnosis of other dementias such as Parkinson’s disease.
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