Response prediction of radiotherapy in lung cancer patients using multimodal data
Pretreatment demographic, radiological, and physiological characteristics were associated with RT response in lung cancer patients. The developed BPNN models leveraging multimodal data effectively predicted PR and PD, to guide personalized treatment strategies and to identify patients unlikely to benefit from RT.
Authors
- Yushun Gong
- Yongqin Li (ORCID: https://orcid.org/0000-0002-6114-2382)
- Xiaojuan Duan (ORCID: https://orcid.org/0000-0002-1613-2927)
- Chen Lu
- Xin Song (ORCID: https://orcid.org/0000-0002-1509-6223)
- Wei Liang (ORCID: https://orcid.org/0000-0002-2703-6965)
Institutions
- Army Medical University (CN)
- Dalian Medical University (CN)
- Second Affiliated Hospital of Chongqing Medical University (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Southwest Hospital (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Journal of Applied Clinical Medical Physics
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1002/acm2.70277
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36