Multi-modal machine learning classifier for idiopathic pulmonary fibrosis predicts mortality in interstitial lung diseases.

Journal: Respiratory investigation
Published Date: Aug 6, 2025

Abstract

BACKGROUND: Interstitial lung disease (ILD) prognostication incorporates clinical history, pulmonary function testing (PFTs), and chest CT pattern classifications. The machine learning classifier, Fibresolve, includes a model to help detect CT patterns associated with idiopathic pulmonary fibrosis (IPF). We developed and tested new Fibresolve software to predict outcomes in patients with ILD.

Authors

  • Sean J Callahan
    University of North Carolina School of Medicine, 321 S. Columbia St, Chapel Hill, 27599, NC, USA. Electronic address: Sean_callahan@med.unc.edu.
  • Mary Beth Scholand
    University of Utah Health, 50 N Medical Dr, Salt Lake City, 84132, UT, USA.
  • 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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