Empirical Validation of Conformal Prediction for Trustworthy Skin Lesions Classification

Understand

Background and objective: Uncertainty quantification is a pivotal field that contributes to realizing reliable and robust systems.

• It becomes instrumental in fortifying safe decisions by providing complementary information, particularly within high-risk applications.
• existing studies have explored various methods that often operate under specific assumptions or necessitate substantial modifications to the network architecture to effectively account for uncertainties.
• The objective of this paper is to study Conformal Prediction, an emerging distribution-free uncertainty quantification technique, and provide a comprehensive understanding of the advantages and limitations inherent in various methods within the medical imaging field.