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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 Filippi1,3

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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