eXplainable Artificial Intelligence (XAI) in aging clock models.

Journal: Ageing research reviews
Published Date:

Abstract

XAI is a rapidly progressing field of machine learning, aiming to unravel the predictions of complex models. XAI is especially required in sensitive applications, e.g. in health care, when diagnosis, recommendations and treatment choices might rely on the decisions made by artificial intelligence systems. AI approaches have become widely used in aging research as well, in particular, in developing biological clock models and identifying biomarkers of aging and age-related diseases. However, the potential of XAI here awaits to be fully appreciated. We discuss the application of XAI for developing the "aging clocks" and present a comprehensive analysis of the literature categorized by the focus on particular physiological systems.

Authors

  • Alena Kalyakulina
    Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, 603022 Nizhny Novgorod, Russia.
  • Igor Yusipov
    Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, 603022 Nizhny Novgorod, Russia.
  • Alexey Moskalev
    George Mason University, Fairfax, VA, United States.
  • Claudio Franceschi
    Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky University, Nizhny, Russia.
  • Mikhail Ivanchenko
    Institute of Information Technology, Mathematics and Mechanics, National Research Lobachevsky State University of Nizhniy Novgorod, Nizhniy Novgorod, Russia.