Analysis of Incursive Breast Cancer in Mammograms Using YOLO, Explainability, and Domain Adaptation
Published:Nov 28, 2025 08:48
•1 min read
•ArXiv
Analysis
The article focuses on the application of YOLO, explainability techniques, and domain adaptation for analyzing incursive breast cancer in mammograms. This suggests a research-oriented approach to improve the accuracy and interpretability of breast cancer detection using AI.
Key Takeaways
- •Applies YOLO, a real-time object detection system, to mammogram analysis.
- •Employs explainability techniques to understand the AI's decision-making process.
- •Utilizes domain adaptation to improve the model's performance across different datasets or imaging techniques.
- •Aims to enhance the accuracy and interpretability of breast cancer detection.
Reference
“The article's focus on YOLO, explainability, and domain adaptation indicates a sophisticated approach to medical image analysis.”