Published on in Vol 8 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65178, first published .
Unsupervised Deep Learning of Electronic Health Records to Characterize Heterogeneity Across Alzheimer Disease and Related Dementias: Cross-Sectional Study

Unsupervised Deep Learning of Electronic Health Records to Characterize Heterogeneity Across Alzheimer Disease and Related Dementias: Cross-Sectional Study

Unsupervised Deep Learning of Electronic Health Records to Characterize Heterogeneity Across Alzheimer Disease and Related Dementias: Cross-Sectional Study

Journals

  1. Fang S, Yin Z, Cai Q, Li L, Zheng P, Chen L. Harnessing artificial intelligence for brain disease: advances in diagnosis, drug discovery, and closed-loop therapeutics. Frontiers in Neurology 2025;16 View
  2. Stern A, Linial M. Integrative machine learning approach to risk prediction for dementia and Alzheimer’s disease. GeroScience 2025 View
  3. Breithaupt A, Tang A, Paolillo E, Bibars M, Johnson E, Saloner R, Possin K, Windon C, Hill-Jarrett T, Giorgio J, Rauschecker A, Kwon H, Vonk J, Pinheiro-Chagas P. Review of Artificial Intelligence for Clinical Use in Alzheimer's Disease and Related Dementias. Seminars in Neurology 2025 View