Attention-guided framework for integrative omics and temporal dynamics in predicting major pathological response in neoadjuvant immunochemotherapy for NSCLC
The multiomics model, integrating multi-temporal, multi-sequence data with attention-based feature fusion, improves MPR prediction in patients with NSCLC receiving neoadjuvant immunochemotherapy, enabling personalized treatment by identifying responders and optimizing outcomes.
Authors
- Xiangfeng Gan (ORCID: https://orcid.org/0000-0001-5839-0468)
- Yi Liang (ORCID: https://orcid.org/0000-0002-6440-6144)
- Shijiancong Liu
- Wenzeng Chen
- Xiaohui Duan (ORCID: https://orcid.org/0000-0002-2224-0887)
- Jianzhong He
- Liangzhan Lv
- Qingdong Cao (ORCID: https://orcid.org/0000-0003-4306-543X)
- Baishen Chen
- Wenhao Li (ORCID: https://orcid.org/0000-0003-0717-9069)
- Wei Zhang (ORCID: https://orcid.org/0009-0002-3507-4504)
Institutions
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
- Zhongshan People's Hospital (CN)
- Fifth Affiliated Hospital of Sun Yat-sen University (CN)
Publication Details
- Journal
- Journal for ImmunoTherapy of Cancer
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1136/jitc-2025-012526
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08