Artificial intelligence in prediction of non-alcoholic fatty liver disease and fibrosis.

Journal: Journal of gastroenterology and hepatology
Published Date: Mar 1, 2021

Abstract

Artificial intelligence (AI) has become increasingly widespread in our daily lives, including healthcare applications. AI has brought many new insights into better ways we care for our patients with chronic liver disease, including non-alcoholic fatty liver disease and liver fibrosis. There are multiple ways to apply the AI technology on top of the conventional invasive (liver biopsy) and noninvasive (transient elastography, serum biomarkers, or clinical prediction models) approaches. In this review article, we discuss the principles of applying AI on electronic health records, liver biopsy, and liver images. A few common AI approaches include logistic regression, decision tree, random forest, and XGBoost for data at a single time stamp, recurrent neural networks for sequential data, and deep neural networks for histology and images.

Authors

  • Grace Lai-Hung Wong
    Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Pong-Chi Yuen
    Hong Kong Baptist University, Hong Kong.
  • Andy Jinhua Ma
    Hong Kong Baptist University, Hong Kong.
  • Anthony Wing-Hung Chan
    Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Shatin, Hong Kong.
  • Howard Ho-Wai Leung
    Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Shatin, Hong Kong.
  • Vincent Wai-Sun Wong
    Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.

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