BioinformaticsbioRxivPreprint
Discernibility in explanations: an approach to designing more acceptable and meaningful machine learning models for medicine
Haomiao Wang, Julien Aligon, Julien May…·Paul Monsarrat
This paper introduces discernibility as a metric to evaluate the clarity of explanations in machine learning models for medicine, finding that the dcor metric best captures user-perceived relationships between data and explanations.
DOI 10.1101/2025.04.06.647498