This deep learning framework provides a clinically adaptable method of obtaining high accuracy classification signatures for Alzheimer’s disease (AD) from MRI data; it was validated against data from 4 independent cohorts, neuropathological findings and expert-driven assessment.
Why this matters
The current diagnostic specificity for AD is between 44.3% and 70.8%. Recent studies have demonstrated ways to derive high accuracy predictions from MRI data through deep learning approaches such as convolutional neural networks for MRI and classification of cognitive status. The use of deep learning approaches in the classification of AD status is crucial in improving patient care.