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Correction

Correction: Redundancy-Aware Topic Modeling for Patient Record Notes

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The images for Figure 3 and Figure 5 were incorrectly switched. Please view the correct images and legends here.

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Figure 3. Topics learnxled by Red-LDA (top) and Vanilla LDA (bottom) on the EHR corpus.

Both topics are about breast cancer (ca is an abbreviation for cancer). The Vanilla LDA topic, however, contains unrelated yet highly ranked words (e.g., eye, glaucoma, colonoscopy, albuterol). The Red-LDA topic was preferred by the domain experts.

https://doi.org/10.1371/journal.pone.0087555.g003

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Figure 5. Red-LDA generative story.

https://doi.org/10.1371/journal.pone.0087555.g005

Reference

  1. 1. Cohen R, Aviram I, Elhadad M, Elhadad N (2014) Redundancy-Aware Topic Modeling for Patient Record Notes. PLoS ONE 9(2): e87555

Citation: The PLOS ONE Staff (2014) Correction: Redundancy-Aware Topic Modeling for Patient Record Notes. PLoS ONE 9(11): e114677. https://doi.org/10.1371/journal.pone.0114677

Published: November 24, 2014

Copyright: © 2014 The PLOS ONE Staff. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.