Representation and Normalization of Complex Interventions for Evidence Computing.

Journal: Studies in health technology and informatics
Published Date: Jun 6, 2022

Abstract

Complex interventions are ubiquitous in healthcare. A lack of computational representations and information extraction solutions for complex interventions hinders accurate and efficient evidence synthesis. In this study, we manually annotated and analyzed 3,447 intervention snippets from 261 randomized clinical trial (RCT) abstracts and developed a compositional representation for complex interventions, which captures the spatial, temporal and Boolean relations between intervention components, along with an intervention normalization pipeline that automates three tasks: (i) treatment entity extraction; (ii) intervention component relation extraction; and (iii) attribute extraction and association. 361 intervention snippets from 29 unseen abstracts were included to report on the performance of the evaluation. The average F-measure was 0.74 for treatment entity extraction on an exact match and 0.82 for attribute extraction. The F-measure for relation extraction of multi-component complex interventions was 0.90. 93% of extracted attributes were correctly attributed to corresponding treatment entities.

Authors

  • Zhehuan Chen
    Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Hao Liu
    Key Laboratory of Development and Maternal and Child Diseases of Sichuan Province, Department of Pediatrics, Sichuan University, Chengdu, China.
  • Stan Liao
    Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA.
  • Marguerite Bernard
    Institute of Human Nutrition, Columbia University, New York, NY, USA.
  • Tian Kang
    Department of Biomedical Informatics, Columbia University, New York, USA.
  • Latoya A Stewart
    Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA.
  • Chunhua Weng
    Department of Biomedical Informatics, Columbia University.

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