Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder.

Journal: BMC medical informatics and decision making
Published Date: Dec 30, 2020

Abstract

BACKGROUND: Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and MetaMap are among the most widely used tools to extract biomedical concept entities. However, their performance in extracting disease-specific terminology from literature has not been compared extensively, especially for complex neuropsychiatric disorders with a diverse set of phenotypic and clinical manifestations.

Authors

  • Jacqueline Peng
    School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
  • Mengge Zhao
    Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
  • James Havrilla
    Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
  • Cong Liu
    Department of Bioengineering, University of Illinois at Chicago, 851 S Morgan St, Chicago, IL, 60607, USA.
  • Chunhua Weng
    Department of Biomedical Informatics, Columbia University.
  • Whitney Guthrie
    Center for Autism Research, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
  • Robert Schultz
    University of Pennsylvania, Philadelphia, PA.
  • Kai Wang
    Department of Rheumatology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, China.
  • Yunyun Zhou
    Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA. yzhou.umc@gmail.com.

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