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Using Unsupervised Learning to Identify Clinical Subtypes of Alzheimer's Disease in Electronic Health Records
Nonie Alexander
,
Daniel C Alexander
,
Frederik Barkhof
,
Spiros Denaxas
January 2020
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Type
Journal article
Publication
Studies in health technology and informatics
Related
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P1-554 DISCOVERING SUBTYPES OF ALZHEIMER�S DISEASE USING ELECTRONIC HEALTH RECORDS
Effect on life expectancy of temporal sequence in a multimorbidity cluster of psychosis, diabetes, and congestive heart failure among 1˙ 7 million individuals in Wales with 20-year follow-up: a retrospective cohort study using linked data
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.
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