DLI-IT: a deep learning approach to drug label identification through image and text embedding.

Journal: BMC medical informatics and decision making
Published Date: Apr 15, 2020

Abstract

BACKGROUND: Drug label, or packaging insert play a significant role in all the operations from production through drug distribution channels to the end consumer. Image of the label also called Display Panel or label could be used to identify illegal, illicit, unapproved and potentially dangerous drugs. Due to the time-consuming process and high labor cost of investigation, an artificial intelligence-based deep learning model is necessary for fast and accurate identification of the drugs.

Authors

  • Xiangwen Liu
    Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Rd, Jefferson, AR, 72079, USA.
  • Joe Meehan
    FDA/National Center for Toxicological Research, 3900 NCTR Rd, Jefferson, AR, 72079, USA.
  • Weida Tong
    National Center for Toxicological Research, Division of Bioinformatics and Biostatistics, U.S. Food and Drug Administration, Jefferson, AR, United States.
  • Leihong Wu
    Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Rd, Jefferson, AR, 72079, USA. Leihong.wu@fda.hhs.gov.
  • Xiaowei Xu
    Department of Information Science, University of Arkansas, Little Rock, Arkansas, United States of America.
  • Joshua Xu
    Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Rd, Jefferson, AR, 72079, USA.

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