Longevity Briefs: Using Machine Learning to Diagnose Alzheimer’s Disease

Posted on 15 September 2020

Longevity briefs provides a short summary of a novel research, medicine, or technology that caught the attention of our researchers in Oxford, due to its potential to improve our health, wellbeing, and longevity.

Why is this research important: There is currently no cure for Alzheimer’s disease, but detecting it early during development can significantly improve outcomes for Alzheimer‘s patients.

What did the researchers do: This paper proposes a neural network that, using brain MRI (magnetic resonance imaging), can differentiate subjects with Alzheimer’s disease from those with mild cognitive impairment and from those with no cognitive impairment. The network makes this classification by comparing the complex patterns of degeneration that are visible in MRI images. This neural network was tested on structural MRI data from 465 subjects, 132 of which had Alzheimer’s disease.

Key takeaway(s) from this research: The proposed method achieved 97.77% accuracy, outperforming current state of the art methods and making this algorithm a promising tool for the diagnosis of Alzheimer’s disease.

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