Artificial Intelligence for Predicting HER2 Status of Gastric Cancer Based on Whole‐Slide Histopathology Images: A Retrospective Multicenter Study (Adv. Sci. 10/2025)
Gastric cancer DiaGnosticsThe frontispiece design centers on a Phoenix, symbolizing rebirth and transformation, reflecting HER2Net's groundbreaking impact on gastric cancer diagnostics.The pink and purple parts of the tail feathers reflect H&E pathological slide images, and the brown sections of the tail feathers symbolize HER2Net's capability to predict HER2 status based on these H&E image, showcasing its precision and integration of AI in medical technology.More details can be found in article number 2408451 by Liang Zhao and co-workers.
Authors
- Yuhan Liao (ORCID: https://orcid.org/0009-0007-4624-646X)
- Xiaojin Wu (ORCID: https://orcid.org/0000-0003-3894-0631)
- Yunfei Zhi (ORCID: https://orcid.org/0000-0002-0084-6810)
- H. Zeng (ORCID: https://orcid.org/0009-0002-7101-0495)
- Xiaoqing Zhuo (ORCID: https://orcid.org/0000-0003-4784-9661)
- Xiaofeng Zeng (ORCID: https://orcid.org/0000-0002-3883-2318)
- Shupeng Hu
- Donghui Zhang (ORCID: https://orcid.org/0000-0002-1269-0796)
- Xinhua Chen (ORCID: https://orcid.org/0000-0002-1879-4318)
- Hao Xu (ORCID: https://orcid.org/0000-0003-2000-0561)
- Liang Zhao (ORCID: https://orcid.org/0000-0002-1429-0884)
- Bing Chen
Publication Details
- Journal
- Advanced Science
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1002/advs.202570067
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00