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.

LMIC WebMaster • September 1, 2023

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