Extractive Clinical Question-Answering With Multianswer and Multifocus Questions: Data Set Development and Evaluation Study.

Journal: JMIR AI
Published Date: Jun 20, 2023

Abstract

BACKGROUND: Extractive question-answering (EQA) is a useful natural language processing (NLP) application for answering patient-specific questions by locating answers in their clinical notes. Realistic clinical EQA can yield multiple answers to a single question and multiple focus points in 1 question, which are lacking in existing data sets for the development of artificial intelligence solutions.

Authors

  • Sungrim Moon
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • Huan He
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • Heling Jia
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • Hongfang Liu
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • Jungwei Wilfred Fan
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.

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