Data‐assisted differential diagnosis of dementia by deep neural networks using MRI: A study from the European DLB consortium

Clinicopathological overlap between neurodegenerative diseases contributes to challenging differentiation between dementia types. Improving differential diagnosis is important to provide optimal patient care and better predict future needs. Deep learning techniques such as convolutional neural networks have in recent years gained much attention for their high performance in image classification. Magnetic resonance imaging (MRI) computer‐assisted diagnosis (CAD) systems based on deep learning could potentially contribute to increased reliability of clinical diagnosis.