P1-554 DISCOVERING SUBTYPES OF ALZHEIMER�S DISEASE USING ELECTRONIC HEALTH RECORDS
Daniel C Alexander
Alzheimer’s & Dementia
Identifying and evaluating clinical subtypes of Alzheimers disease in care electronic health records using unsupervised machine learning
Using Unsupervised Learning to Identify Clinical Subtypes of Alzheimer's Disease in Electronic Health Records
Impact on life expectancy of temporal sequencing in a multimorbidity cluster of psychosis, diabetes, and congestive heart failure using linked data for 1.7 million individuals in Wales with 20-year follow-up
ClustEHR: a tool for generating synthetic EHR data for unsupervised learning experiments.
UK phenomics platform for developing and validating EHR phenotypes: CALIBER