Transfer learning‐trained convolutional neural networks identify novel MRI biomarkers of Alzheimer's disease progression

Abstract

Genome‐wide association studies (GWAS) for late onset Alzheimer's disease (AD) may miss genetic variants relevant for delineating disease stages when using clinically defined case/control as a phenotype due to its loose definition and heterogeneity.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2021
Source ID
10.1002/dad2.12140

Entities

People

  • Annat Haber
  • Asli Uyar
  • Benjamin A. Logsdon
  • Cai John
  • Christoph Preuss
  • Gregory W. Carter
  • Hongtian Stanley Yang
  • R. Krishna Murthy Karuturi
  • The Alzheimer’s Disease Neuroimaging Initiative*
  • Vivek Philip
  • Yi Li

Organizations

  • Jackson Laboratory
  • National Institute of Biomedical Imaging and Bioengineering
  • National Institute on Aging
  • National Institutes of Health
  • Sage Bionetworks
  • United States Department of Defense

Tags

Fields of Study

  • Biology
  • Psychology

Readers

  • Joint Military Operations and Doctrine.
  • Molecular and genetic basis of cancer.
  • Neuroscience

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Biotechnology