Explainable AI predicting Alzheimer's disease with latent multimodal deep neural networks.

Journal: Journal of biopharmaceutical statistics
Published Date: Jun 18, 2025

Abstract

PURPOSE: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline. We proposed a novel latent multimodal deep learning framework to predict AD cognitive status using clinical, neuroimaging, and genetic data.

Authors

  • Xi Chen
    Department of Critical care medicine, Shenzhen Hospital, Southern Medical University, Guangdong, Shenzhen, China.
  • Jeffrey Thompson
    Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA. jthompson21@kumc.edu.
  • Zijun Yao
    University of Kansas, Lawrence, KS, USA.
  • Joseph C Cappelleri
    Biostatistics, Pfizer Inc., Groton, CT, USA.
  • Jonah Amponsah
    Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.
  • Rishav Mukherjee
    Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.
  • Jinxiang Hu
    Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.

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