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.

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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
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article

Foundation Model for Predicting Prognosis and Adjuvant Therapy Benefit From Digital Pathology in GI Cancers

Nicholas J. Hawkins, Ruijiang Li, Jinxi Xiang, Jitendra Jonnagaddala et al.
14 citations
Journal of Clinical Oncology
Radiomics and Machine Learning in Medical Imaging
19.04
article

Foundation Model for Predicting Prognosis and Adjuvant Therapy Benefit From Digital Pathology in GI Cancers

Nicholas J. Hawkins, Ruijiang Li, Jinxi Xiang, Jitendra Jonnagaddala, Xiaofeng Jiang, Jing Zhang, Xiyue Wang, Kun‐Hsing Yu, Guoxin Li, Robyn L. Ward, Wei Yuan, Yuming Jiang, Sen Yang, Yuchen Li, Wei Wang, Xiao Ming Zhang, Yijiang Chen, Xiaoyan Wu, Fang Wang
article en
14 citations

Abstract

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.

Journal of Clinical OncologyVol. 43(32)
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)
Openalex Percentile: Top 0%
Radiomics and Machine Learning in Medical Imaging
19.04
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