Artificial intelligence for Alzheimer’s disease: Promise or challenge?

Carlo Fabrizio, Andrea Termine, Carlo Caltagirone, Giulia Sancesario

Research output: Contribution to journalArticlepeer-review

Abstract

Decades of experimental and clinical research have contributed to unraveling many mechanisms in the pathogenesis of Alzheimer’s disease (AD), but the puzzle is still incomplete. Although we can suppose that there is no complete set of puzzle pieces, the recent growth of open data-sharing initiatives collecting lifestyle, clinical, and biological data from AD patients has provided a potentially unlimited amount of information about the disease, far exceeding the human ability to make sense of it. Moreover, integrating Big Data from multi-omics studies provides the potential to explore the pathophysiological mechanisms of the entire biological continuum of AD. In this context, Artificial Intelligence (AI) offers a wide variety of methods to analyze large and complex data in order to improve knowledge in the AD field. In this review, we focus on recent findings and future challenges for AI in AD research. In particular, we discuss the use of Computer-Aided Diagnosis tools for AD diagnosis and the use of AI to potentially support clinical practices for the prediction of individual risk of AD conversion as well as patient stratification in order to finally develop effective and personalized therapies.

Original languageEnglish
Article number1473
JournalDiagnostics
Volume11
Issue number8
DOIs
Publication statusPublished - Aug 2021

Keywords

  • Alzheimer’s disease
  • Artificial intelligence
  • Diagnosis
  • Machine learning

ASJC Scopus subject areas

  • Clinical Biochemistry

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