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Epistatic Features and Machine Learning Improve Alzheimer's Risk Prediction Over Polygenic Risk Scores
BiologymedRxiv preprint

Epistatic Features and Machine Learning Improve Alzheimer's Risk Prediction Over Polygenic Risk Scores

S. Hermes, J. Cady, et al.

Discover how a team of researchers, including Stephen Hermes and Carlos Cruchaga, has developed a groundbreaking paragenic risk score that significantly enhances the prediction of late-onset Alzheimer's disease. This innovative model harnesses epistatic interactions and advanced machine learning techniques, offering a nuanced approach that outperforms traditional polygenic risk scores. Dive into this compelling study and learn about its promising implications for improving lifetime risk assessment!... show more
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