Nature Biomedical Engineering

Tackling prediction uncertainty in machine learning for healthcare

• The article emphasizes the need for prediction-uncertainty metrics in healthcare applications, particularly radiology.
• It discusses the implementation of these metrics in error-intolerant and error-tolerant applications.
• It provides a framework for understanding prediction uncertainty in healthcare.
• It highlights the need for machine-learning models with zero tolerance for false-positive or false-negative errors.

https://www.nature.com/articles/s41551-022-00988-x