Machine Learning and Computed Tomography Radiomics to Predict Disease Progression to Upfront Pembrolizumab Monotherapy in Advanced Non-Small-Cell Lung Cancer: A Pilot Study
This pragmatic model offers a valuable tool to guide first-line treatment decisions in NSCLC patients with high PD-L1 expression and has the potential to advance personalized oncology and improve timely disease management.
Authors
- Stephen Lam (ORCID: https://orcid.org/0000-0002-3964-1492)
- Calum MacAulay (ORCID: https://orcid.org/0000-0003-4440-2792)
- Gang Wang (ORCID: https://orcid.org/0000-0002-0225-4173)
- Cheryl Ho (ORCID: https://orcid.org/0000-0002-5922-3984)
- Ian Janzen (ORCID: https://orcid.org/0000-0001-7473-7329)
- Ren Yuan
- Barbara Melosky (ORCID: https://orcid.org/0000-0003-2865-659X)
- Jessica Li (ORCID: https://orcid.org/0000-0003-1869-6117)
- Ye Qian (ORCID: https://orcid.org/0000-0002-9720-168X)
Institutions
- University of British Columbia (CA)
Publication Details
- Journal
- Cancers
- Published
- 2024-12-28
- DOI
- https://doi.org/10.3390/cancers17010058
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- BC Cancer Foundation