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Updated: Aug 10, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Quantifying generalization error in machine learning prediction of cognitive decline

Roya Melanie Hüppi1, Nicolas Langer2, Bruno Hebling Vieira2

  • 1Methods of Plasticity Research, Department of Psychology, University of Zurich, 8050, Zurich, Zurich, Switzerland; Neuroscience Center Zurich (ZNZ), University of Zurich & ETH Zurich, 8057, Zurich, Zurich, Switzerland; Department of Adult Psychiatry and Psychotherapy, Psychiatric University Clinic Zurich and University of Zurich, 8032, Zurich, Zurich, Switzerland.

The Journal of Prevention of Alzheimer'S Disease
|August 8, 2026
PubMed
Summary

Adding structural MRI data significantly improves machine learning predictions of cognitive decline. While generalizability across datasets is reduced, this enhances precision medicine for early intervention.

Keywords:
Cognitive declineGeneralizabilityMachine learningPredictive modelingStructural MRI

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