Data augmentation is a popular technique which helps improve generalization capabilities of deep neural networks, and can be perceived as implicit regularization. It plays a pivotal role in scenarios in which the amount of high-quality ground-truth data is limited, and acquiring new examples is costly and time-consuming. This is a very common problem in medical […]

Alzheimer’s disease (AD), the most common tauopathy, is an age-dependent, progressive neurodegenerative disease. Epidemiological studies implicate the role of genetic background in the onset and progression of AD. Despite mutations in familial AD, several risk factors have been implicated in sporadic AD, of which the onset is unknown. In AD, there is a sequential and […]

Alzheimer’s disease (AD) is marked by the presence of amyloid beta (Aβ) plaques, neurofibrillary tangles (NFT), neuronal death and synaptic loss, and inflammation in the brain. AD research has, in large part, been dedicated to the understanding of Aβ and NFT deposition as well as to the pharmacological reduction of these hallmarks. However, recent GWAS […]