Communications Medicine (Oct 2022)

Interpretable machine learning prediction of all-cause mortality

  • Wei Qiu,
  • Hugh Chen,
  • Ayse Berceste Dincer,
  • Scott Lundberg,
  • Matt Kaeberlein,
  • Su-In Lee

DOI
https://doi.org/10.1038/s43856-022-00180-x
Journal volume & issue
Vol. 2, no. 1
pp. 1 – 15

Abstract

Read online

Qui et al. present a new approach, IMPACT, that uses explainable artificial intelligence to analyze all-cause mortality. IMPACT provides insights into the individualized mortality risk scores, while maintaining high model accuracy and the expressive power to capture complex, non-linear relationships between mortality and individuals’ features.