Computed tomography machine learning classifier correlates with mortality in interstitial lung disease.

Journal: Respiratory investigation
Published Date: May 20, 2024

Abstract

BACKGROUND: A machine learning classifier system, Fibresolve, was designed and validated as an adjunct to non-invasive diagnosis in idiopathic pulmonary fibrosis (IPF). The system uses a deep learning algorithm to analyze chest computed tomography (CT) imaging. We hypothesized that Fibresolve is a useful predictor of mortality in interstitial lung diseases (ILD).

Authors

  • Onofre Moran-Mendoza
    Interstitial Lung Diseases Program, Division of Respirology and Sleep Medicine, Queen's University, 102 Stuart Street, Kingston, Ontario, K7L 2V7, Canada.
  • Abhishek Singla
    Division of Pulmonary, Critical Care and Sleep Medicine, University of Cincinnati, 231 Albert Sabin Way, ML 0564, Cincinnati, OH, 45267-0564, United States.
  • Angad Kalra
    Department of Computer Science, University of Toronto, Toronto, Ontario, Canada. Electronic address: angadk@cs.toronto.edu.
  • Michael Muelly
    Imvaria, Inc, USA.
  • Joshua J Reicher
    Stanford Health Care and Palo Alto Veterans Affairs, Palo Alto, CA, USA.

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