Central Reading of Ulcerative Colitis Clinical Trial Videos Using Neural Networks.

Journal: Gastroenterology
Published Date: Feb 1, 2021

Abstract

BACKGROUND AND AIMS: Endoscopic disease activity scoring in ulcerative colitis (UC) is useful in clinical practice but done infrequently. It is required in clinical trials, where it is expensive and slow because human central readers are needed. A machine learning algorithm automating the process could elevate clinical care and facilitate clinical research. Prior work using single-institution databases and endoscopic still images has been promising.

Authors

  • Klaus Gottlieb
    Eli Lilly and Company, Indianapolis, Indiana. Electronic address: klaus.gottlieb@lilly.com.
  • James Requa
    Docbot Inc, Irvine, California, USA.
  • William Karnes
    Department of Medicine, University of California, Irvine, California; H.H. Chao Comprehensive Digestive Disease Center, University of California, Irvine, California.
  • Ranga Chandra Gudivada
    Eli Lilly and Company, Indianapolis, Indiana.
  • Jie Shen
    Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital, Wannan Medical College, Wuhu, Anhui 241001, China; Pharmacy School, Wannan Medical College, Wuhu, Anhui 241002, China; Department of Clinical Pharmacy, Yijishan Hospital, Wannan Medical College, Wuhu, Anhui 241001, China; Anhui Provincial Engineering Research Center for Polysaccharides Drugs, Wannan Medical College, Wuhu, Anhui 241001, China.
  • Efren Rael
    Docbot Inc, Irvine, California.
  • Vipin Arora
    Eli Lilly and Company, Indianapolis, Indiana.
  • Tyler Dao
    Docbot Inc, Irvine, California, USA.
  • Andrew Ninh
    Docbot Inc, Irvine, California, USA.
  • James McGill
    Eli Lilly and Company, Indianapolis, Indiana.

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