Automated Measurements of Muscle Mass Using Deep Learning Can Predict Clinical Outcomes in Patients With Liver Disease.

Journal: The American journal of gastroenterology
PMID: 32467506

Abstract

INTRODUCTION: There is increasing recognition of the central role of muscle mass in predicting clinical outcomes in patients with liver disease. Muscle size can be extracted from computed tomography (CT) scans, but clinical implementation will require increased automation. We hypothesize that we can achieve this by using artificial intelligence.

Authors

  • Nicholas C Wang
    Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, MI, USA.
  • Peng Zhang
    Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
  • Elliot B Tapper
    Department of Medicine, University of Michigan Medical School, Ann Arbor, Michigan, MI, USA.
  • Sameer Saini
    Division of Gastroenterology, University of Michigan, Ann Arbor, Michigan, USA.
  • Stewart C Wang
    Department of Surgery, University of Michigan Medical School, Ann Arbor, Michigan, MI , USA.
  • Grace L Su
    Michigan Medicine, Department of Internal Medicine, Division of Gastroenterology and Hepatology, Ann Arbor, Michigan, United States of America.

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