Summary Objectives The KNee OsteoArthritis Prediction (KNOAP2020) challenge was
organized to objectively compare methods for the prediction of incident symptomatic …

Background Several studies indicate that the anterior visual pathway provides information
about the dynamics of axonal degeneration in Multiple Sclerosis (MS). Current research in …

Studying small effects or subtle neuroanatomical variation requires large-scale sample size
data. As a result, combining neuroimaging data from multiple datasets is necessary …

More than 50 million older people worldwide are suffering from dementia, and this number is
estimated to increase to 150 million by 2050. Greater caregiver burdens and financial …

Healthcare data are inherently multimodal. Almost all data generated and acquired during a
patient's life can be hypothesized to contain information relevant to providing optimal …

Abstract Introduction In Alzheimer's disease (AD), cognitive decline is driven by various
interlinking causal factors. Systems thinking could help elucidate this multicausality and …

Robust forecasting of the future anatomical changes inflicted by an ongoing disease is an
extremely challenging task that is out of grasp even for experienced healthcare …

Abstract Machine learning methods exploiting multi-parametric biomarkers, especially
based on neuroimaging, have huge potential to improve early diagnosis of dementia and to …

Accurate and realistic simulation of high-dimensional medical images has become an
important research area relevant to many AI-enabled healthcare applications. However …

Abstract Background In Alzheimer's disease, amyloid-β (A β) peptides aggregate in the
lowering CSF amyloid levels-a key pathological hallmark of the disease. However, lowered …