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Artificial Intelligence for Alzheimer’s Disease: Promise or Challenge?

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...

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Detalles Bibliográficos
Autores principales: Fabrizio, Carlo, Termine, Andrea, Caltagirone, Carlo, Sancesario, Giulia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391160/
https://www.ncbi.nlm.nih.gov/pubmed/34441407
http://dx.doi.org/10.3390/diagnostics11081473
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author Fabrizio, Carlo
Termine, Andrea
Caltagirone, Carlo
Sancesario, Giulia
author_facet Fabrizio, Carlo
Termine, Andrea
Caltagirone, Carlo
Sancesario, Giulia
author_sort Fabrizio, Carlo
collection PubMed
description 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.
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spelling pubmed-83911602021-08-28 Artificial Intelligence for Alzheimer’s Disease: Promise or Challenge? Fabrizio, Carlo Termine, Andrea Caltagirone, Carlo Sancesario, Giulia Diagnostics (Basel) Review 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. MDPI 2021-08-14 /pmc/articles/PMC8391160/ /pubmed/34441407 http://dx.doi.org/10.3390/diagnostics11081473 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Fabrizio, Carlo
Termine, Andrea
Caltagirone, Carlo
Sancesario, Giulia
Artificial Intelligence for Alzheimer’s Disease: Promise or Challenge?
title Artificial Intelligence for Alzheimer’s Disease: Promise or Challenge?
title_full Artificial Intelligence for Alzheimer’s Disease: Promise or Challenge?
title_fullStr Artificial Intelligence for Alzheimer’s Disease: Promise or Challenge?
title_full_unstemmed Artificial Intelligence for Alzheimer’s Disease: Promise or Challenge?
title_short Artificial Intelligence for Alzheimer’s Disease: Promise or Challenge?
title_sort artificial intelligence for alzheimer’s disease: promise or challenge?
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391160/
https://www.ncbi.nlm.nih.gov/pubmed/34441407
http://dx.doi.org/10.3390/diagnostics11081473
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