Automatic label checking: The missing step in making reliable medical AI
Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in large radiographic collections. By automatically verifying body-part, projection, and rotation tags, their research improves deep-learning models used for routine clinical tasks and research projects.
Deep-learning models using chest radiography have made remarkable progress in recent years, evolving to accomplish tasks that are challenging for humans such as estimating cardiac and respiratory function.
However, AIs are only as good as the images ...