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bioRxiv · 10.1101/062307

An Empirical Analysis of Topic Modeling for Mining Cancer Clinical Notes

Katherine Redfield Chang·Xinghua Lou·Theofanis Karaletsos·Chris Crosbie·Stuart Gardos·David Artz·Gunnar Ratsch
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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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Katherine Redfield Chang, Xinghua Lou, Theofanis Karaletsos, Chris Crosbie, Stuart Gardos, David Artz, Gunnar Ratsch. 2016-07-06. An Empirical Analysis of Topic Modeling for Mining Cancer Clinical Notes. https://doi.org/10.1101/062307

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