In this thesis, we investigated brain aging using different simple and complex models through brain age estimation using IDPs extracted from brain MRI.We have also applied simple methods and machine learning explainability models to identify the most informative features to model brain age. We further estimated brain age for fiber groups within brain white matter tracts. In addition, we revealed the effects of daily life style, cardiac risk factors and morbidity in brain aging. Finally, we used causal models to explore the role of TL in healthy aging and Alzheimer’s disease in unhealthy aging to cause alterations within brain structures and functions.

Imaging Genetics through Brain Age Estimation and Image Derived Phenotypes

Ahmed Mahdee Abdo Salih
Investigation
;
Gloria Menegaz
Supervision
;
Ilaria Boscolo
Supervision
;
2022-01-01

Abstract

In this thesis, we investigated brain aging using different simple and complex models through brain age estimation using IDPs extracted from brain MRI.We have also applied simple methods and machine learning explainability models to identify the most informative features to model brain age. We further estimated brain age for fiber groups within brain white matter tracts. In addition, we revealed the effects of daily life style, cardiac risk factors and morbidity in brain aging. Finally, we used causal models to explore the role of TL in healthy aging and Alzheimer’s disease in unhealthy aging to cause alterations within brain structures and functions.
Brain aging, MRI, machine learning
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Descrizione: The thesis is divided into six chapters with the first one as introduction for the following chapters. In each chapter, there are sections that shows the used data and methods
Tipologia: Tesi di dottorato
Licenza: Dominio pubblico
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1067434
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