Vine copulas decompose multivariate EHR distributions into hierarchical bivariate conditional dependencies for variable ranking, subset selection, and probabilistic mining of comorbidities.
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An ensemble deep clustering framework combined with traditional methods ranks highest across 14 clustering techniques on real EHR data for heart failure patients from the All of Us program.
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Vine Copulas for Analyzing Multivariate Conditional Dependencies in Electronic Health Records Data
Vine copulas decompose multivariate EHR distributions into hierarchical bivariate conditional dependencies for variable ranking, subset selection, and probabilistic mining of comorbidities.
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Mining Electronic Health Records to Investigate Effectiveness of Ensemble Deep Clustering
An ensemble deep clustering framework combined with traditional methods ranks highest across 14 clustering techniques on real EHR data for heart failure patients from the All of Us program.