Conformal Prediction of Residual Cognition in Aging and Alzheimer’s Disease
2024

Predicting Cognitive Resilience in Aging and Alzheimer's Disease

publication

Author Information

Author(s): Essien Ime, McDaniel Laura, Walston Jeremy, Bennett David, Abadir Peter, Chellappa Rama

Primary Institution: Johns Hopkins University

Hypothesis

How can we model residual cognition to understand cognitive resilience in aging and Alzheimer's disease?

Conclusion

The study provides insights into cognitive resilience by identifying cases where cognitive function does not align with neuropathological burden.

Supporting Evidence

  • The study examines cognitive resilience in the context of Alzheimer's disease.
  • It models residual cognition as the difference between observed and expected cognitive function.
  • Conformal prediction is used to generate prediction intervals for cognitive scores.

Takeaway

This study looks at how some people can think well even when their brains show signs of Alzheimer's, helping us understand how to keep our minds healthy as we age.

Methodology

The study uses conformal prediction to model residual cognition based on beta-amyloid and tau protein levels and demographic data.

Participant Demographics

Participants were stratified into control, asymptomatic AD, and AD groups based on clinical consensus diagnosis at time of death.

Digital Object Identifier (DOI)

10.1093/geroni/igae098.3644

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