Habitat radiomics analysis for progression free survival and immune-related adverse reaction prediction in non-small cell lung cancer treated by immunotherapy
By leveraging machine learning to predict the outcomes of ICIs, we can move closer to achieving tailored ICIs for lung cancer. This advancement will assist physicians in selecting and managing subsequent treatment strategies, thereby facilitating clinical decision-making.
Authors
- Yi Chen (ORCID: https://orcid.org/0009-0009-9770-5632)
- Mengzhe Zhang (ORCID: https://orcid.org/0000-0003-0682-1574)
- Renhua Guo (ORCID: https://orcid.org/0000-0003-4475-8617)
- Jiali Xu (ORCID: https://orcid.org/0000-0001-7047-7240)
- Yuemin Wu
- Zhihong Zhang (ORCID: https://orcid.org/0000-0002-5779-9365)
- Wei Zhang (ORCID: https://orcid.org/0000-0002-6508-364X)
- Qi Liang (ORCID: https://orcid.org/0000-0002-0054-1478)
- Yanan Cui (ORCID: https://orcid.org/0000-0003-3579-0690)
- Jiali Dai (ORCID: https://orcid.org/0000-0003-4509-1391)
- Tongfu Yu
- Wenxin Zhou
- Yuqin Jiang
- Xiao Liang (ORCID: https://orcid.org/0009-0007-6881-4210)
- Chen Zhang (ORCID: https://orcid.org/0000-0001-8706-1372)
- Pengpeng Zhang
- Jun Li (ORCID: https://orcid.org/0009-0004-1683-5130)
Institutions
- Tianjin Medical University Cancer Institute and Hospital (CN)
- Jiangsu Province Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Journal of Translational Medicine
- Published
- 2025-04-03
- DOI
- https://doi.org/10.1186/s12967-024-06057-y
- Citations
- 8
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 10.88
Funders
- Innovative Research Group Project of the National Natural Science Foundation of China
- National Natural Science Foundation of China