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Interpretable machine learning-driven biomarker identification and validation for Alzheimer’s disease

28 Dec 2024

Abstract excerpt

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by limited effective treatments, underscoring the critical need for early detection and diagnosis to improve intervention outcomes. This study integrates various bioinformatics methodologies with interpretable machine learning to identify reliable biomarkers for AD diagnosis and treatment. By leveraging differentially expressed genes (DEGs)...

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PMID: 39730451
DOI: 10.1038/s41598-024-80401-6

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