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

Sean J Callahan¹, Mary Beth Scholand², Angad Kalra³, Michael Muelly³, Joshua J Reicher³

¹University of North Carolina School of Medicine, 321 S. Columbia St, Chapel Hill, 27599, NC, USA. Electronic address: Sean_callahan@med.unc.edu.

²University of Utah Health, 50 N Medical Dr, Salt Lake City, 84132, UT, USA.

³IMVARIA Inc., 1748 Shattuck Ave Pmb 137, Berkeley, 94709, CA, USA.

PubMed DOI

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. MET…

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