Foundation Model for Predicting Prognosis and Adjuvant Therapy Benefit From Digital Pathology in GI Cancers
The pathology foundation model can accurately predict survival outcomes and complement clinicopathologic factors in GI cancers. Pending prospective validation, it may be used to improve risk stratification and inform personalized adjuvant therapy.
Authors
- Nicholas J. Hawkins (ORCID: https://orcid.org/0000-0002-2204-3189)
- Ruijiang Li (ORCID: https://orcid.org/0000-0002-0232-5998)
- Jinxi Xiang (ORCID: https://orcid.org/0000-0002-5476-3690)
- Jitendra Jonnagaddala (ORCID: https://orcid.org/0000-0002-9912-2344)
- Xiaofeng Jiang (ORCID: https://orcid.org/0000-0002-3716-8232)
- Jing Zhang (ORCID: https://orcid.org/0000-0003-2663-053X)
- Xiyue Wang (ORCID: https://orcid.org/0000-0002-3597-9090)
- Kun‐Hsing Yu (ORCID: https://orcid.org/0000-0001-9892-8218)
- Guoxin Li (ORCID: https://orcid.org/0000-0003-2773-7048)
- Robyn L. Ward (ORCID: https://orcid.org/0000-0002-6877-8906)
- Wei Yuan (ORCID: https://orcid.org/0000-0002-3158-3486)
- Yuming Jiang (ORCID: https://orcid.org/0000-0001-6184-3931)
- Sen Yang (ORCID: https://orcid.org/0000-0003-3125-6626)
- Yuchen Li (ORCID: https://orcid.org/0000-0002-1594-2717)
- Wei Wang (ORCID: https://orcid.org/0000-0002-5273-3332)
- Xiao Ming Zhang (ORCID: https://orcid.org/0000-0001-5327-8506)
- Yijiang Chen (ORCID: https://orcid.org/0000-0002-3224-4339)
- Xiaoyan Wu (ORCID: https://orcid.org/0000-0003-1761-2532)
- Fang Wang (ORCID: https://orcid.org/0000-0002-8808-8531)
Institutions
- Qingdao University (CN)
- The University of Sydney (AU)
- Harvard University (US)
- Sun Yat-sen University (CN)
- Sichuan University (CN)
- Yuhuangding Hospital (CN)
- UNSW Sydney (AU)
- West China Hospital of Sichuan University (CN)
- Nanfang Hospital (CN)
- Fresenius (Germany) (DE)
- Sun Yat-sen University Cancer Center (CN)
- Beijing Tsinghua Chang Gung Hospital (CN)
- Wake Forest University (US)
- Southern Medical University (CN)
- Stanford University (US)
- Tsinghua University (CN)
Publication Details
- Journal
- Journal of Clinical Oncology
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1200/jco-24-01501
- Citations
- 14
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 19.04