Researchers improve algorithm that detects Alzheimer’s from MRI images

The latest studies have shown that pre-trained convolutional neural networks (CNN) can accurately diagnose cognitive disease from brain magnetic resonance images. Photo: Pexels

(Emily Henderson/ News Medical Net) — Lithuanian researchers from Kaunas University of Technology (KTU) improved an algorithm that detects Alzheimer’s disease from magnetic resonance imaging (MRI) images. The new model achieved over 98 per cent accuracy on a test dataset in detecting the neurodegenerative disease by improving a neural network model.

Alzheimer’s disease (AD) is the seventh in the U.S. and one of the leading causes of death in the world. Patients with AD often experience memory loss and cognitive decline due to the impairment and death of nerve cells in the brain.

Usually, to diagnose this disease a psychiatric evaluation has to be performed, memory and problem-solving skills must be tested, or various brain scans, including MRI, have to be performed. Detecting an early stage of AD is an especially difficult task. (…)

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