Artificial intelligence model predicts M2 macrophage levels and HCC prognosis with only globally labeled pathological images
Our models effectively predicted M2 macrophage levels and HCC prognosis. The findings suggest that our models offer a novel method for determining biomarker levels and forecasting prognosis, eliminating additional clinical tests, thereby delivering substantial clinical benefits.
Authors
- Lingfei Kong (ORCID: https://orcid.org/0000-0002-7426-3589)
- Dujuan Li
- Qiankun Luo (ORCID: https://orcid.org/0000-0002-6423-0847)
- Tao Qin (ORCID: https://orcid.org/0000-0001-8791-3555)
- Yingjie Tian (ORCID: https://orcid.org/0000-0002-4675-0398)
- Huiyuan Tian
- Minfan Zhao (ORCID: https://orcid.org/0009-0008-4524-4830)
Institutions
- University of Science and Technology of China (CN)
- Zhengzhou University (CN)
- Henan Provincial People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2024-12-20
- DOI
- https://doi.org/10.3389/fonc.2024.1474155
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.40