Dementia Diagnosis Classification Using Deep Learning Neural Networks Based on Clock Drawing Test (CDT) and Medicare claims

Mengyao Hu
Assistant Research Scientist, Survey Research Center, Institute for Social Research

Co-Investigators

  • Yi Lu Murphey, University of Michigan-Dearborn

Abstract

This pilot study will develop advanced deep learning neural networks to analyze Clock-Drawing Test images to predict dementia diagnosis. The pilot will draw upon Medicare claims linked with a large, publicly available repository of clock images from the 2011-2019 National Health and Aging Trends Study, a panel study of Medicare beneficiaries ages 65 and older. 

Outcomes

  • Hu, Mengyao; Murphey, Yi Lu; Wang, Song Qin Tian; Zhao Zixuan; Gonzalez, Richard; Freedman Vicki A.; Zahodne Laura (2022) Exploring the Use of Deep Learning Neural Networks to Improve Dementia Detection: Automating Coding of the Clock-Drawing Test. NHATS/NSOC Research in Progress Seminar, Ann Arbor, Michigan.