Research in computer analysis of medical images bears many promises to improve patients'
health. However, a number of systematic challenges are slowing down the progress of the …

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a
driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted …

Around a third of the total population of Europe suffers from mental disorders. The use of
electroencephalography (EEG) together with Machine Learning (ML) algorithms to diagnose …

Background Early and accurate diagnosis of Alzheimer's disease (AD) is essential for
disease management and therapeutic choices that can delay disease progression. Machine …

This work validates the generalizability of MRI-based classification of Alzheimer's disease
(AD) patients and controls (CN) to an external data set and to the task of prediction of …

Beyond detecting brain lesions or tumors, comparatively little success has been attained in
identifying brain disorders such as Alzheimer's disease (AD), based on magnetic resonance …

This study examines the impact of sample size on predicting cognitive and mental health
phenotypes from brain imaging via machine learning. Our analysis shows a 3-to 9-fold …

Dementia is one of the leading causes of severe cognitive decline, it induces memory loss
and impairs the daily life of millions of people worldwide. In this work, we consider the …

The Alzheimer′ s Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge is
the most comprehensive challenge to date with regard to the number of subjects, considered …

Alzheimer's disease (AD) is a degenerative disorder that leads to progressive, irreversible
cognitive decline. To obtain an accurate and timely diagnosis and detect AD at an early …