Integrating computed tomography and biopsy images to predict chemotherapy response in gastric cancer
By integrating pathological images and CT features, we can maximize the utilization of pre-treatment information and enhance the accuracy of NAC prediction in AGC.
Authors
- Yonghe Chen
- Shenyan Zhang (ORCID: https://orcid.org/0009-0007-3015-8350)
- Yu Luo (ORCID: https://orcid.org/0000-0002-2333-1457)
- Tao Luo (ORCID: https://orcid.org/0000-0001-9979-6587)
- Lei Lian (ORCID: https://orcid.org/0000-0002-8895-7792)
- Kaikai Wei
- Barry Chi Hong Lai (ORCID: https://orcid.org/0000-0002-6061-7155)
- Yi Lin (ORCID: https://orcid.org/0000-0002-1556-6416)
Institutions
- Sun Yat-sen University (CN)
- Sixth Affiliated Hospital of Sun Yat-sen University (CN)
- Chinese University of Hong Kong, Shenzhen (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-10-21
- DOI
- https://doi.org/10.3389/fonc.2025.1666358
- Primary Topic
- Gastric Cancer Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation for Young Scientists of Shanxi Province
- Young Scientists Fund