Alzheimer's disease (AD) is a heterogeneous neurodegenerative disorder and is the most
common cause of dementia. Furthermore, aging is considered the most critical risk factor for …

The anticipation of progression of Alzheimer's disease (AD) is crucial for evaluations of
secondary prevention measures thought to modify the disease trajectory. However, it is …

Abstract Background Currently, Alzheimer's disease (AD) cohort datasets are difficult to find
and lack across-cohort interoperability, and the actual content of publicly available datasets …

In the past, methods to subtype or biotype patients using brain imaging data have been
developed. However, it is unclear whether and how these trained machine learning models …

A clinical diagnosis of Alzheimer's disease dementia (ADD) encompasses considerable
pathological and clinical heterogeneity. While Alzheimer's disease patients typically show a …

Background: Despite numerous past endeavors for the semantic harmonization of
Alzheimer's disease (AD) cohort studies, an automatic tool has yet to be developed …

Individual organizations, such as hospitals, pharmaceutical companies, and health
insurance providers, are currently limited in their ability to collect data that are fully …

Background While the amyloid/tau/neurodegeneration (ATN) framework has found wide
application in Alzheimer's disease research, it is unclear if thresholds obtained using distinct …

Two Cox-based multistate modeling approaches are compared for analyzing a complex
multicohort event history process. The first approach incorporates cohort information as a …

Abstract Background Previous models of Alzheimer's disease (AD) progression were
primarily hypothetical or based on data originating from single cohort studies. However …