As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI.

Journal: BMC medical informatics and decision making
Published Date: Sep 11, 2020

Abstract

BACKGROUND: We focus on the importance of interpreting the quality of the labeling used as the input of predictive models to understand the reliability of their output in support of human decision-making, especially in critical domains, such as medicine.

Authors

  • Federico Cabitza
    Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milano, Italy.
  • Andrea Campagner
    IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi, 4, 20161, Milano, Italy. Electronic address: a.campagner@campus.unimib.it.
  • Luca Maria Sconfienza
    Unit of Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Galeazzi, Milan, Italy.

Keywords

External Resources

Popular Topics
Recent Journals