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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
[Hierarchical attention-driven multiple instance learning for clear cell renal cell carcinoma grading and staging in
Jianing Xu1, Yixiao Mao1, Yu Zhang1
1School of Biomedical Engineering//Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou 510515, China.
Summary
A new hierarchical attention-driven multiple instance learning (HA-MIL) framework precisely grades and stages clear cell renal cell carcinoma (ccRCC). This AI-powered tool enhances pathological analysis, offering improved accuracy over traditional methods.
Area of Science:
- Digital pathology
- Machine learning in oncology
- Renal cell carcinoma research