Novel deep learning model to assess Alzheimer's disease progression risk

By Pooja Toshniwal PahariaOct 3 2023Reviewed by Lily Ramsey, LLM In a recent study published in eClinical Medicine, researchers analyzed disease progression to identify distinct patterns in the Alzheimer's disease trajectory using Mendelian randomization and deep learning .

About the study In the present study, researchers developed and validated a novel DL-based model to assess the risk of progression through different stages of cognitive decline. A Mendelian randomization study was also conducted to evaluate the causal associations between the identified patterns and Alzheimer's disease development.

Only clinical characteristics with less than 30% missing data in every dataset were included to guarantee that useful clinical features were chosen. The chosen ADNI participants had 1.5 and 3.0 T magnetic resonance imaging data retrieved.

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