AI-based association analysis for medical imaging using latent-space geometric confounder correction.

This study addresses the challenges of confounding effects and interpretability in artificial-intelligence-based medical image analysis. Whereas existing literature often resolves confounding by removing confounder-related information from latent representations, this strategy risks affecting image reconstruction quality in generative models, thus limiting their applicability in feature visualization. To tackle this, we propose a different strategy that retains confounder-related information in latent representations while finding an alternative confounder-free representation of the image data.

Social health and prevention of dementia: Integration of human and mice studies.

Objectives: Prevention of dementia is considered a healthcare priority. We aimed to identify potentially modifiable risk factors and mechanisms within the social health domain to find novel avenues to prevent cognitive decline and dementia.

Design: We integrated the results of eight sub-studies of the Social Health in Mice and Men (SHiMMy) project that were separately published in specialized journals, but not yet jointly considered.

Validation of a novel neuroimaging signature for dementia and clinical Alzheimer's disease in the population-based Rotterdam study.

Background: A novel neuroimaging signature of regional cortical thickness on brain MRI recently showed high potential for Alzheimer's disease and related dementias (ADRD) risk stratification in the community. How these findings translate to other populations, remains undetermined.

Objective: We aimed to replicate this novel ADRD neuroimaging marker in the population-based Rotterdam Study.

[Gender differences in career paths in medical academia: a nationwide study in the Netherlands].

Objective: To determine gender differences in career progression of physicians.

Design: Retrospective cohort study.

Method: We examined career progression until 2023 of 715 physicians who received their PhD in the Netherlands in 2007/2008.

Preconceptional brain structure and future conception: a prospective brain MRI study among 321 women.

Brain structure may influence female fertility through its reciprocal relationship with the endocrine system, but this hypothesis is underexplored. This study investigated the association between preconceptional brain structure and the likelihood of conception in a prospective population-based neuroimaging cohort. Women intending to conceive within a year were recruited and structural brain MRI scans were collected from 321 participants between June 2019 and March 2021.