Novel Deep Learning Method Provides Early and Accurate Differential Diagnosis for Parkinsonian Diseases

A new deep learning method has been created to aid in the diagnosis of parkinsonian diseases, according to research published ahead of print by The Journal of Nuclear Medicine. Using a 3D deep convolutional neural network to extract deep metabolic imaging indices from 18F-FDG PET scans, scientists can effectively differentiate between Parkinson’s disease and other parkinsonian syndromes, such as multiple system atrophy and progressive supranuclear palsy.

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