Clinically Explainable Prediction of Immunotherapy Response Integrating Radiomics and Clinico-Pathological Information in Non-Small Cell Lung Cancer
Our study therefore not only improves the prediction of immunotherapy response in patients with NSCLC from multimodal data but also assists the clinicians in making clinically interpretable predictions by providing language-based explanations.
Authors
- Rajat Thawani (ORCID: https://orcid.org/0000-0002-5378-9434)
- Jhimli Mitra (ORCID: https://orcid.org/0000-0002-2347-7210)
- Soumya Ghose (ORCID: https://orcid.org/0000-0002-2730-1482)
Institutions
- Oregon Health & Science University (US)
- GE Global Research (United States) (US)
Publication Details
- Journal
- Cancers
- Published
- 2025-08-18
- DOI
- https://doi.org/10.3390/cancers17162679
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08