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Activity Number: 367
Type: Invited
Date/Time: Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #310926 View Presentation
Title: Feature Allocation Models for Phenotype Discovery
Author(s): Finale Doshi-Velez*+
Companies: Harvard
Keywords: feature allocation model ; phenotype discovery ; Indian Buffet Process
Abstract:

Clustering models are frequently used to find similar subgroups in a larger population. In medicine, clustering models are frequently used subtype patients into groups with similar disease characteristics, known as phenotypes. However, patients with complex conditions may express not one, but several phenotypes. Feature allocation models provide an approach to model this one-to-many relationship.

Here, we describe two feature allocation models for phenotype discovery, both built from the Indian Buffet Process. The first allows one to specify a prior distribution over the number of features independently for each observation. The second uses available knowledge of relationships between dimensions to produce sparser phenotype descriptions. We show that being able to incorporate covariates and other expert knowledge improves interpretability without sacrificing predictive power, a feature important to scientists and clinicians.


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