Expert guided natural language processing using one-class classification.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Jun 10, 2015

Abstract

INTRODUCTION: Automatically identifying specific phenotypes in free-text clinical notes is critically important for the reuse of clinical data. In this study, the authors combine expert-guided feature (text) selection with one-class classification for text processing.

Authors

  • Erel Joffe
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Texas Department of Hematology and Bone Marrow Transplantation, Tel Aviv Medical Center, Tel Aviv Israel.
  • Emily J Pettigrew
    Department of Computer Science, Rice University, Houston, Texas.
  • Jorge R Herskovic
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Texas The University of Texas, M.D. Anderson Cancer Center, Houston, Texas.
  • Charles F Bearden
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Texas.
  • Elmer V Bernstam
    Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA.

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