Article

Evaluating Fairness and Generalizability of Alzheimer’s Disease Diagnosis Models Trained on Racially Imbalanced Datasets

2025-10-02

Abstract excerpt

Alzheimer’s disease (AD) is a major global health concern, expected to affect 12.7 million Americans by 2050. Machine learning (ML) algorithms have been developed for AD diagnosis and progression prediction, but the lack of racial/ethnic diversity in clinical datasets raises concerns about their generalizability across demographic groups, particularly underrepresented populations. Studies show ML algorithms inheri...

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Literature Corpus work: 8786c276-4f34-5a60-83f6-273321cbc32f
DOI: 10.1101/2025.09.30.678854

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