Normative modeling is an emerging and innovative framework for map** individual
differences at the level of a single subject or observation in relation to a reference model. It …

The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly develo** and …

Magnetic resonance imaging and computed tomography from multiple batches (eg sites,
scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to …

Abstract The Dominantly Inherited Alzheimer Network (DIAN) is an international
collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from …

Removing the bias and variance of multicentre data has always been a challenge in large
scale digital healthcare studies, which requires the ability to integrate clinical features …

We present a review of the characterization of healthy brain aging using MRI with an
emphasis on morphology, lesions, and quantitative MR parameters. A scope review found …

Staging amyloid-beta (Aβ) pathophysiology according to the intensity of neurodegeneration
could identify individuals at risk for cognitive decline in Alzheimer's disease (AD). In blood …

Increasingly large MRI neuroimaging datasets are becoming available, including many
highly multi-site multi-scanner datasets. Combining the data from the different scanners is …

Medical imaging is a central part of clinical diagnosis and treatment guidance. Machine
learning has increasingly gained relevance because it captures features of disease and …

Clinical neuroimaging data availability has grown substantially in the last decade, providing
the potential for studying heterogeneity in clinical cohorts on a previously unprecedented …