Machine learning and XAI approaches highlight the strong connection between $$O_3$$ O 3 and $$NO_2$$ N O 2 pollutants and Alzheimer’s disease

Machine learning and XAI approaches highlight the strong connection between $$O_3$$ O 3 and $$NO_2$$ N O 2 pollutants and Alzheimer’s disease

Abstract Alzheimer’s disease (AD) is the most common type of dementia with millions of affected patients worldwide. Currently, there is still no cure and AD is often diagnosed long time after onset because there is no clear diagnosis. Thus, it is essential to study the physiology and pathogenesis of...

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Bibliographic Details
Main Authors: Alessandro Fania, Alfonso Monaco, Nicola Amoroso, Loredana Bellantuono, Roberto Cazzolla Gatti, Najada Firza, Antonio Lacalamita, Ester Pantaleo, Sabina Tangaro, Alena Velichevskaya, Roberto Bellotti
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Scientific Reports
Subjects:
Alzheimer
Machine learning
Explainable artificial intelligence
Pollution
Standardized mortality ratio (SMR)
One health
Online Access:https://doi.org/10.1038/s41598-024-55439-1

Internet

https://doi.org/10.1038/s41598-024-55439-1

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