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Peer-Reviewed Publication
BMC Pulm Med2024;24(1):254.May 23, 2024Journal Article

Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data.

Kavitha C Selvan1, Joshua Reicher2,3, Michael Muelly2,3, Angad Kalra3, Ayodeji Adegunsoye4
1Section of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Chicago Medicine, 5841 S Maryland Avenue, Chicago, IL, 60637, USA. kavitha.selvan@uchicagomedicine.org.
2Department of Radiology, Stanford University, Stanford, CA, USA.
3IMVARIA Inc, 2390 Domingo Ave. #1496, Berkley, CA, 94705, USA.
4Section of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Chicago Medicine, 5841 S Maryland Avenue, Chicago, IL, 60637, USA.
PubMed PMC DOI PDF

Abstract

BACKGROUND: Mortality prediction in interstitial lung disease (ILD) poses a significant challenge to clinicians due to heterogeneity across disease subtypes. Currently, forced vital capacity (FVC) and Gender, Age, and Physiology (GAP) score are the two most utilized metrics in prognostication. Recently, a machine learning classifier system, Fibresolve, designed to identify a variety of computed to…

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