Sensitivity of CT-derived radiomic features to extraction libraries and gray-level discretization in the context of immune biomarker discovery
Our study emphasizes the need to select stable CT-derived handcrafted features to build immunotherapy biomarkers, which is a necessary precursor for multi-institutional validation of imaging biomarkers.
Authors
- Philippe Desprès (ORCID: https://orcid.org/0000-0001-8926-4050)
- Sevinj Yolchuyeva (ORCID: https://orcid.org/0000-0001-6760-1546)
- Yannick Lemaréchal (ORCID: https://orcid.org/0000-0002-2494-2831)
- Leyla Ebrahimpour (ORCID: https://orcid.org/0000-0001-7243-8296)
- Venkata Manem (ORCID: https://orcid.org/0000-0003-1427-2819)
- Michèle Orain (ORCID: https://orcid.org/0000-0002-9779-1851)
- Fabien Lamaze
- Philippe Joubert (ORCID: https://orcid.org/0000-0001-7784-6387)
- François Coulombe (ORCID: https://orcid.org/0000-0002-6273-227X)
- Arnaud Driussi
Institutions
- Lung Institute (US)
- Cancer Research Center (US)
- Institut universitaire de cardiologie et de pneumologie de Québec (CA)
- Université Laval (CA)
- Université du Québec à Trois-Rivières (CA)
Publication Details
- Journal
- British Journal of Radiology
- Published
- 2024-09-16
- DOI
- https://doi.org/10.1093/bjr/tqae187
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- Université Laval
- Institut de Valorisation des Données
- Fonds de Recherche du Québec - Santé