Automatic categorization of self-acknowledged limitations in randomized controlled trial publications.

Journal: Journal of biomedical informatics
Published Date: Mar 26, 2024

Abstract

OBJECTIVE: Acknowledging study limitations in a scientific publication is a crucial element in scientific transparency and progress. However, limitation reporting is often inadequate. Natural language processing (NLP) methods could support automated reporting checks, improving research transparency. In this study, our objective was to develop a dataset and NLP methods to detect and categorize self-acknowledged limitations (e.g., sample size, blinding) reported in randomized controlled trial (RCT) publications.

Authors

  • Mengfei Lan
    School of Information Sciences, University of Illinois Urbana-Champaign, 501 Daniel Street, Champaign, 61820, IL, USA.
  • Mandy Cheng
    Department of Biological Sciences, Binghamton University, 4400 Vestal Parkway East, New York City, 13902, NY, USA.
  • Linh Hoang
    University of Illinois at Urbana-Champaign, Champaign, IL.
  • Gerben Ter Riet
    Department of General Practice, Academic Medical Center, Amsterdam, The Netherlands.
  • Halil Kilicoglu
    School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, IL 61820, United States.

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