Achievability to Extract Specific Date Information for Cancer Research.

Journal: AMIA ... Annual Symposium proceedings. AMIA Symposium
Published Date: Mar 4, 2020

Abstract

Accurate identification of temporal information such as date is crucial for advancing cancer research which often requires precise date information associated with related cancer events. However, there is a gap for existing natural language processing (NLP) systems to identify dates for specific cancer research studies. Illustrated with two case studies, we investigated the feasibility, evaluated the performances and discussed the challenges of date information extraction for cancer research.

Authors

  • Liwei Wang
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
  • Jason Wampfler
    Mayo Clinic, Rochester, MN, USA.
  • Angela Dispenzieri
    Division of Hematology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Hua Xu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Ping Yang
    Key Laboratory of Grain and Oil Processing and Food Safety of Sichuan Province, College of Food and Bioengineering, Xihua University Chengdu 610039 China xingyage1@163.com.
  • Hongfang Liu
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.

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