Machine Learning-based Prediction Models for Diagnosis and Prognosis in Inflammatory Bowel Diseases: A Systematic Review.

Journal: Journal of Crohn's & colitis
Published Date: Mar 14, 2022

Abstract

BACKGROUND AND AIMS: There is increasing interest in machine learning-based prediction models in inflammatory bowel diseases [IBD]. We synthesised and critically appraised studies comparing machine learning vs traditional statistical models, using routinely available clinical data for risk prediction in IBD.

Authors

  • Nghia H Nguyen
    Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla, CA, USA.
  • Dominic Picetti
    Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla, CA, USA.
  • Parambir S Dulai
    Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla, CA, USA.
  • Vipul Jairath
    Department of Epidemiology and Biostatistics, Western University, London, ON, Canada.
  • William J Sandborn
    University of California San Diego, La Jolla, California.
  • Lucila Ohno-Machado
    University of California San Diego, La Jolla, CA.
  • Peter L Chen
    HyperPlanar, San Diego, CA, USA.
  • Siddharth Singh
    Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla, CA, USA.

Keywords

External Resources

Popular Topics
Recent Journals