Benchmarking Real-World Medical Image Classification with Noisy Labels: A Critical Review

This ArXiv article highlights the challenges of medical image classification when dealing with noisy labels, a common issue in real-world datasets. The study provides valuable insights into the practical aspects and future directions of improving image classification models.

• •Addresses the practical challenges of using AI for medical image analysis.
• •Focuses on the impact of label noise on model performance.
• •Provides a forward-looking perspective on improving image classification techniques.