Abstract #3758

Automatic classification of patients with Alzheimer’s disease (AD) and mild cognitive impairment (MCI) who will convert to AD using deep neural networks

Federica Agosta¹, Silvia Basaia¹, Luca Wagner², Giuseppe Magnani³, and Massimo Filippi^1,3

¹Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, ²Effeventi, Milan, Italy, ³Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy

We built and validated a deep learning algorithm that predicts the individual diagnosis of Alzheimer’s disease (AD) and the development of AD in mild cognitive impairment (MCI) patients based on a single cross-sectional brain structural MRI scan. The deep neural network (DNN) procedure discriminated AD and heathy controls with an accuracy up to 98%, and MCI converters and MCI stable with an accuracy up to 75%. DNNs provide a powerful tool for the automatic classification of AD and MCI prognosis.

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