An Empirical Analysis of Topic Modeling for Mining Cancer Clinical Notes
Katherine Redfield Chang, Xinghua Lou, Theofanis Karaletsos, Christopher Crosbie, Stuart Gardos, David Artz, Gunnar Rätsch
Abstract
Using a variety of techniques including Topic Modeling, Principal Component Analysis and Bi-clustering, we explore electronic patient records in the form of unstructured clinical notes and genetic mutation test results. Our ultimate goal is to gain insight into a unique body of clinical data, specifically regarding the topics discussed within the note content and relationships between patient clinical notes and their underlying genetics.
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